By Nic Lewis
I showed in my May 10th article Why herd immunity to COVID-19 is reached much earlier than thought that inhomogeneity within a population in the susceptibility and in the social-connectivity related infectivity of individuals would reduce, in my view probably very substantially, the herd immunity threshold (HIT), beyond which an epidemic goes into retreat. I opined, based on my modelling, that the HIT probably lay somewhere between 7% and 24%, and that evidence from Stockholm County suggested it was around 17% there, and had been reached. Mounting evidence supports my reasoning.[1]
I particularly want to highlight an important paper published on July 24th “Herd immunity thresholds estimated from unfolding epidemics” (Aguas et al.).[2] The author team is much the same as that of the earlier theoretical paper (Gomes et al.[3]) that prompted my May 10th article.
Aguas et al. used a SEIR compartmental epidemic model modified to allow for inhomogeneity, similar to the model I used although they also considered further variants. They fitted their models to scaled daily new cases data from four European countries for which disaggregated regional case data was also readily available. In all cases they found a better fit from their models incorporating heterogeneity to the standard homogeneous assumption SEIR model. They found that:
Homogeneous models systematically fail to fit the maintenance of low numbers of cases after the relaxation of social distancing measures in many countries and regions.
Aguas et al. estimate the HIT at between 6% and 21% for the countries in their analysis – very much in line with the range I suggested in May. They also found that their HIT estimates were robust to various changes in their model specification. By contrast, if the population were homogeneous or were vaccinated randomly, the estimated HIT would have been around 65% –80%, in line with the classical formula, {1 – 1/R0}, where R0 is the epidemic’s basic reproduction number.[4]
Aguas et al.’s Figure 3, reproduced below, shows how the HIT reduces with increasing variation either in susceptibility (given exposure) or in connectivity, which affects both an individual’s susceptibility (via altering exposure to infection) and infectivity. The coloured dots and vertical lines show the inferred position of each of the four countries they analysed in each of these (separately modelled) cases.
Aguas et al. Fig. 3 Herd immunity threshold with gamma-distributed susceptibility (top) or connectivity related exposure to infection (bottom). Curves generated with the SEIR model (Equation 1-4) assuming values of R0 estimated for the study countries assuming gamma-distributed: susceptibility [top]; connectivity (and hence exposure to infection) [bottom]. Herd immunity thresholds (solid curves) are calculated according to the formula 1 − (1/R0)1/(1 + CV^2) for heterogeneous susceptibility and 1 − (1/R0)1/(1 + 2 CV^2) for heterogeneous connectivity. Final sizes of the corresponding unmitigated epidemics are also shown (dashed).
As Aguas et al. say in their Abstract:
These findings have profound consequences for the governance of the current pandemic given that some populations may be close to achieving herd immunity despite being under more or less strict social distancing measures.
The underlying reason for the classical formula being inapplicable is, as they say:
More susceptible and more connected individuals have a higher propensity to be infected and thus are likely to become immune earlier. Due to this selective immunization by natural infection, heterogeneous populations require less infections to cross their herd immunity threshold than suggested by models that do not fully account for variation.
The Imperial College COVID-19 model (Ferguson et al.[5]) is a prime example of one that does not adequately account for variation in individual susceptibility and connectivity.
Aguas et al. point out that consideration of heterogeneity in the transmission of respiratory infections has traditionally focused on variation in exposure summarized into age-structured contact matrices. They showed that, besides this approach typically ignoring differences in susceptibility given virus exposure, the aggregation of individuals into age groups leads to much lower variability than that they found from fitting the data. The resulting models appeared to differ only moderately from homogeneous approximations.
A key reason for variability in susceptibility to COVID-19 given exposure to the SARS-CoV-2 virus causing is that the immune systems of a substantial proportion (35% to 80%) of unexposed individuals have T-cells, circulating antibodies or other components that are cross-reactive to SARS-CoV-2 and can be expected to provide substantial resistance to it.[6] [7] [8] [9] Such components likely arise from past exposure to common cold or other coronaviruses, or to influenza.[10] Not being specific to SARS-CoV-2, and typically not being antibodies, such immune system components are not normally detected in seroprevalence or other tests for immunity to SARS-CoV-2.
I will end with a follow up to my June 28th article focusing on Sweden. In it, I concluded that it was likely the HIT had been surpassed in the three largest Swedish regions, and in the country as a whole, by the end of April notwithstanding that COVID-19-specific antibodies had only been detected in 6.3% of the population.[11] I also projected, based on their declining trend, that total COVID-19 deaths would likely only be about 6,400. Subsequent developments support those conclusions. Swedish COVID-19 deaths have continued to decline, notwithstanding a return to more travel and less social distancing, and are now down to 10 to 15 a day. According to the latest Financial Times analysis,[12] excess mortality in Sweden over 2020 to date was 5,500, or 24%. That is only about half the excess mortality percentage for the UK (45%), Italy (44%) and Spain (56%), and is also lower than for France (31%), the Netherlands (27%) and Switzerland (26%), despite Sweden not having imposed a lockdown or shut primary schools. Moreover, total mortality in Sweden over the last 24 months is now lower than over the previous 24 months, despite an upward trend in the old age population.
Nicholas Lewis 27 July 2020
Further update 31 July 2020
Another important paper has now been published on the role of inhomogeneity within a population in the social-connectivity related susceptibility and infectivity of individuals and in biological susceptibility: “Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19” (Tkachenko et al.)[13]. The paper’s mathematical/statistical analysis is excellent.[14] Their method of estimating the role of population inhomogeneity in lowering the herd immunity threshold seems reasonable in principle.[15]
However, they estimated the effect of inhomogeneity during lockdowns, and assumed that the effect is the same in other circumstances. But a key effect of social distancing measures, including public events bans, bar and restaurant closures, etc. as well as full lockdowns, is to heavily reduce the number of contacts by the most connected people that are capable of transmitting infection. For people with few social connections, such measures will have a proportionately much smaller effect. So the effect in more normal circumstances of population inhomogeneity in social-connectivity, which appears to be more important than inhomogeneity in biological susceptibility, is bound to be underestimated, quite possibly substantially, by their approach.
Nevertheless, their best fit to New York City COVID-19 data during lockdown gives an estimate of an inhomogeneity factor[16] λ of 4.5.[17] An alternative estimation method based on a cross-sectional regression across US States gives a λ estimate of 5.3.[18]
A middle of the range λ value of 4.9 implies a HIT of 20% if R0 = 3.0 (16.4% if R0 = 2.4; 24.6% if R0 = 4; 28.0% if R0 = 5). It also equates, if all the inhomogeneity is social-connectivity related, to a coefficient of variation (CV)[19] of 1.4 – which is the geometrical mean of the two CV values (1 and 2) that I used in my original article.
Estimating λ from fits to the NYC or Chicago data prior to lockdown implies much higher CV estimates, in the range 2.4 to 2.9 if all inhomogeneneity is social-connectivity related, in non-lockdown circumstances. The corresponding estimates for nine of the worst hit US States range from 1.9 to 3.4.[20]
[1] One example, further supporting my superspreader-based evidence of variability in social connectivity, is Miller et al: Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel medRxiv 22 May 2020 https://doi.org/10.1101/2020.05.21.20104521 This paper shows that 1-10% of infected individuals caused 80% of infections. That points to variability in social connectivity related susceptibility and infectivity quite likely being higher than I modelled .
[2] Aguas, R. and co-authors: Herd immunity thresholds estimated from unfolding epidemics” medRxiv 24 July 2020 https://doi.org/10.1101/2020.07.23.20160762
[3] Gomes, M. G. M., et al.: Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold. medRxiv 2 May 2020. https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v1
[4] The basic reproduction number of an epidemic, R0, measures how many people, on average, each infected individual infects at the start of the epidemic. If R0 exceeds one, the epidemic will grow, exponentially at first. But, assuming recovered individuals are immune, the pool of susceptible individuals shrinks over time and the current reproduction number falls. The proportion of the population that have been infected at the point where the current reproduction number falls to one is the ‘herd immunity threshold’ (HIT). Beyond that point the epidemic is under control, and shrinks.
[5] Neil M Ferguson et al.: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. Imperial College COVID-19 Response Team Report 9, 16 March 2020, https://spiral.imperial.ac.uk:8443/handle/10044/1/77482
[6] Grifoni, A.et al.: Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals. Cell 11420, 2020 https://doi.org/10.1016/j.cell.2020.05.015
[7] Braun, J., et al.: Presence of SARS-CoV-2 reactive T cells in COVID-19 patients and healthy donors. medRxiv 22 April 2020 https://www.medrxiv.org/content/10.1101/2020.04.17.20061440v1.
[8] Le Bert, N. et al.: Different pattern of pre-existing SARS-COV-2 specific T cell immunity in SARS-recovered and uninfected individuals. bioRxiv 27 May 2020. https://doi.org/10.1101/2020.05.26.115832
[9] Nelde, A. et al.: SARS-CoV-2 T-cell epitopes define heterologous and COVID-19-induced T-cell recognition. ResearchSquare 16 June 2020. https://www.researchsquare.com/article/rs-35331/v1
[10] Lee, C., Koohy, H., et al.: CD8+ T cell cross-reactivity against SARS-CoV-2 conferred by other coronavirus strains and influenza virus. bioRxiv 20 May 2020. https://doi.org/10.1101/2020.05.20.107292.
[11] Such seroprevalence is likely to significantly understate the proportion of the population who have had COVID-19, since asymptomatic or mild disease often results in undetectably low antibody levels (Long, Q. X. et al.: Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nat Med. 18 June 2020 https://doi.org/10.1038/s41591-020-0965-6 . Such patients will nevertheless be immune to reinfection (Sekine, K. et al.: Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. bioRxiv 29 June 2020 https://doi.org/10.1101/2020.06.29.174888).965-6
[12] https://www.ft.com/content/a26fbf7e-48f8-11ea-aeb3-955839e06441. Data updated to 13 July
[13] Tkachenko, A.V. et al.: Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19. medRxiv 29 July 2020 https://doi.org/10.1101/2020.07.26.20162420
[14] I think its title gives a slightly misleading impression, although that issue is not central to their paper. It is in fact “persistent” heterogeneity that causes “short-term” overdispersion, albeit that over a short period random variability will have a significant influence. I’m unconvinced by their argument that estimating social-connectivity related susceptibility and infectivity from overdispersion in transmission statistics is likely to lead to significant bias, provided that estimation is based on large-scale transmission and not just a few superspreader events.
[15] Doing so involves dependency on an estimate of the infection fatality rate, but their IFR-inferred proportion of the New York City population that had been infected by early June 2020 looks reasonable, based on the NYS survey suggesting 22.7% of NYC residents had been infected by late March and the ratio of cumulative COVID-19 deaths 23 days later.
[16] They term their λ an “immunity factor”, but it is only partly related to biological immunity. If the causative inhomogeneity is related to biological immunity, λ = 1 + CV2, whereas if it is related to social connectivity (which affects infectivity as well as susceptibility) λ = 1 + 2CV2.
[17] They also obtian a similar estimate for Chicago, but based on a much narrower range of data.
[18] Or λ = 4.7 for a selected subset of States.
[19] The ratio of the standard deviation to the mean of a random variable.
[20] I have excluded NY State data, as their curve for that State shows abnormal behaviour, quite likely due to the early epidemic data being strongly dominated by NY City
Originally posted here, where a pdf copy is also available
How can we influence the Coefficient of Variation in Fig. 3?
Lockdown and social distancing measures very likely reduce the connectivity-related Coefficient of Variation, reducing their effectiveness especially if not applied right at the start of an epidemic (being, in this case, January 2020).
Look at what we call ‘the common flu’ numbers just as you did COVID-19, and then consider how the Corrupt Ones have bumped up the numbers, by reassigning ‘what is the cause of death’ at the morgue, and how many more people have died in the Corrupt Controlled Hospitals, while so many other hospitals have empty beds in their intensive care units.
It is absolutely absurd to claim that a CV survivor who died in an auto accident as a COVID-19 DEATH.
We also just found out that people who are being retested for CV, as they want to return to work and cannot work until they test negative, are being counting as another positive person.
This is NOT just a cruel joke. Anyone caught in criminal activity that causes or is linked to deaths or people is murder, and they need to be put down. We cannot allow Hitler-like beings to exist with their evil power over people, nor allow them to teach their evil ways to another person.
This post is consistent with the study coming out of Oxford. One of the co-authors gave an informative interviews with views of the implications for health policies. The interview with Sunetra Gupta is at:
https://reaction.life/we-may-already-have-herd-immunity-an-interview-with-professor-sunetra-gupta/
My synopsis is : Herd Immunity Already?
https://rclutz.wordpress.com/2020/07/24/herd-immunity-already/
The paper is The impact of host resistance on cumulative mortality and the threshold of herd immunity for SARS-CoV-2.
https://www.medrxiv.org/content/10.1101/2020.07.15.20154294v1
The interview with Sunetra Gupta is, IMO, a must read full of loaded wisdom and a very different perspective about infectious disease. This quote especially caught my attention and refers predominately to western attitudes.
“What’s disappointed me about the way this has been approached is it has been approached along a single axis, which, if you like, is a scientific one. Even within that context, you could argue that it’s too one-dimensional, so we’re not thinking about what’s happening with other infectious diseases or how many people are going to die of cancer.
That’s the axis of disease, but then there’s the socioeconomic axis, which has been ignored. But there’s a third, aesthetic access, which is about how we want to live our lives. We are closing ourselves off not just to the disease, but to other aspects of being human.”
This is close to how I have felt about the whole experience of Covid-19 as compared to what went on before it. Why have we become so skewed in our thinking if that is what has happened?
ukweather lass
as you will be aware very many of us have been saying exactly the same thing for many months. we have wildly over reacted and in the process ignored the economy, our own financial health, mental health, ability to work, interact, go to cultural events and all the other things that make life worth while.
the govt has looked on it from a very narrow perspective but things like greater deaths through cancer, heart disease or huge economic problems causing other concerns such as unemployment or a reduction in budgets , seem to have not been considered.
mind you this is all small beer compared to what will be unleashed if we follow the crazies who want to see zero carbon by 2025 or even 2030 or even 2035….
tonyb
” or huge economic problems causing other concerns such as unemployment or a reduction in budgets , seem to have not been considered.”
Those concerns are unwarranted. To get around that we just need to shed the belief in Neoclassical Political Economy and adopt something more Modern.
“At the start of the crisis, I argued that the national governments, which issue their own currency, could take up the entire wage and profits bill if it wanted to – to reduce the ‘economic costs’ of the lockdowns to close to zero.
Unemployment did not have to rise.
Businesses did not have to be destroyed.
If we had an enforceable lockdown and eliminated the virus, with our borders strictly controlled until a credible health solution was introduced, then no economic damage was necessary.
Foster just adopts the neoliberal bias, that dominates the mainstream economics discipline, in assuming that if we have lockdowns there will be devastating GDP losses and elevated unemployment.
Once you understand the fiscal capacity of the Government then the concept of a trade-off seems rather flawed.
The economic losses that have been recorded to date – and they are massive – were avoidable.”
http://bilbo.economicoutlook.net/blog/?p=45472
J:
“…part of the explanation for that phenomenon that you selectively point to is because Trump deliberately provokes “outrage” so he can outrage mine as a way to claim victimhood and increase support among his self-victimizing cult members.”
So Trump is a Democrat. How do you like those apples? He uses the enemies tactics against them. That must be hard to swallow. He didn’t like the media, so he used Trump Media. It appears as derangement because they argue that you can’t do to us what we did to you.
Calling people cult members is missing what’s happening. The Democrats are just as much a cult but more sheepish in general. The Democrats didn’t adapt and they lost in 2016. Are you missing the lefties leaving the party?
Urban cities are burning. Did you get the message yet? No. When Waco burned, there were still true believers.
Early on, someone suggested tthis pandemic is different because it is the first one with social media. And of course 24/7 cable news:
https://rclutz.files.wordpress.com/2020/03/covid19-media-mentions-2.png
This is the first pandemic which involves Donald Trump in an election year. I have found that the best way to interpret national news events and the degree of national media coverage is to ask “does this help or hurt Trump’s chances for re-election”. If it hurts Trump, it becomes the topic of the hour and is breathlessly pushed until something more damaging comes along. Anything helpful to Trump never sees the light of day. Try looking back at the news events of the last couple of years through this prism and determine if I’m just being paranoid. This year, as time runs out before November, the “damage Trump” narratives have begun to stack upon each other in a last ditch effort.
What you said. I made a comment recently on a facebook friend’s page, on the topic of nationalism and patriotism:
“The nation-state is a relatively new invention comprising today’s form of government of a country, which originated in the the idea of the homeland, a people connected to a place, I guess what “un pays” means in French.
Henry Kissinger some years ago remarked that the problem for modern nation-states is they are too small to protect their citizens from global economic and political forces (not to mention pandemics), but too big and diverse to provide a sense of belonging to an ethnic community. Despite what you say about the US, until recently it had excelled in creating an American tribe out of immigrants coming from everywhere, but desiring to be one people; yes, the famous “melting pot” where being an American was the glue holding things together.
Now “identity politics” taught in academia is pitting groups against one another in a class struggle to secure rights for one tribe at the expense of others. Defiance against respect for the flag and anthem is the antithesis of patriotism: love of country, including the land and the people.”
Someone replied:
“Bling nationalism was a contributing factor to some of the greatest evils of the 20th century. Sad to see a governing party trying to stoke those same emotions.”
There it is: If Trump is patriotic, then it is like fascist or communist nationalism, and is to be mourned.
> If it hurts Trump, it becomes the topic of the hour and is breathlessly pushed until something more damaging comes along. Anything helpful to Trump never sees the light of day
This, of course, is only true of you have a very limited definition of “the national media,” crafted so as to confirm a bias (and even there, the description is exaggerated even if it gets the basic pattern correctly).
And if course, part of the explanation for that phenomenon that you selectively point to is because Trump deliberately provokes “outrage” so he can outrage mine as a way to claim victimhood and increase support among his self-victimizing cult members.
Little joshie is a TDS sufferer and TDS denier.
TDS exists, Don, just as did ODS and BDS. Of course it does.
The cult exists also. But you’ll never admit that, will you? That’s the first sign of a cult member.
Breaking news. Very consistent with Dr. Gupta’s study, a new research reports SARS responsive CD4 T-cells in a significant portion of the healthy population.
“We investigated SARS-CoV-2 spike glycoprotein (S)-reactive CD4+ T cells in peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors (HD). We detected SARS-CoV-2 S-reactive CD4+ T cells in 83% of patients with COVID-19 but also in 35% of HD.”
“Our study reveals pre-existing cellular SARS-CoV-2-cross-reactivity in a substantial proportion of SARS-CoV-2 seronegative HD. This finding might have significant epidemiological implications regarding herd immunity thresholds and projections for the COVID-19 pandemic.”
Study is here: https://www.nature.com/articles/s41586-020-2598-9_reference.pdf
My synopsis: https://rclutz.wordpress.com/2020/07/29/sars-cross-immunity-from-t-cells/
https://i2.wp.com/theactivescientist.com/wp-content/uploads/2020/03/T-cell-resps.jpg?resize=768%2C459&ssl=1
Correction: This just popped up at Nature, but it is the same paper as Nic Lewis’ #7 reference.
Nic:
The study you highlighted was based on four European countries. Meanwhile in several of the hotter climate US states virus infections and deaths have surged. Why is this? Has herd immunity been delayed there, is there more homogeneity?
it is speculated that the increase in Florida, Texas, AZ is due to moving into air conditioned space
Other speculations include similar increases in cases on the Mexican side of the border, and transmissions resulting from ongoing street protests after Mar 25. In any case, the new cases are not yet affecting the death rates. Of course, they may be a delayed increase, or it may be that younger people now infected are more resilient.
https://rclutz.files.wordpress.com/2020/07/cases-vs-deaths-4-states.gif
Error: the protests started after May 25, not March.
> . In any case, the new cases are not yet affecting the death rates.
How do you know this?
I see a marked increase in deaths (and hospitalizations) in many locations where vases increased, after a lag of around 3 weeks.
…cases…
And that’s with a marginal improvement in therapeutics.
Yes, it would be good to get an expert opinion on why deaths in hot states are surging as it is continually claimed the virus does not thrive in these conditions.
Is air conditioning a feasible reason, as that would imply that ac was the norm all day and all night in all homes and offices. Is that so? What temperature is the air cooled to? Does the ac itself cause problems through recirculating bad air within an apartment for examples?
Yes I have also heard the immigration over the border with Mexico claim. Again is that credible? PIs there a definite spike as a result of BLM and other protests?
If the virus is not killed by warmth the myth needs to be busted. If there are other causes that cancel out the reality that warmth does kill the virus we need to know about them
Tonyb
tonyb, the logic is that, yes, the sun and hot temperatures outside kill the virus. Indoor, cool, humid spaces help the virus, along with (low quality) AC systems recycling air loaded with virus.
People are using air conditioning in New York and New Jersey and Washington DC, and Connecticut. No spikes there.
I think the main ways it is spreading in the South only indirectly involves air conditioning. It is spreading in churches, restaurants, and bars where people are not wearing masks. Lots of people in close proximity and opening their mouths a lot.
Joshua | July 27, 2020 at 6:11 pm |
“People are using air conditioning in New York and New Jersey and Washington DC, and Connecticut. No spikes there.“
–
Bit hard to get a spike in New York, they have all had it.
Also the number of deaths per number of infections keeps going down overall?
angech –
> Bit hard to get a spike in New York, they have all had it.
I live in NY State. Seroprevalence here is quite low. Much lower than many places spiking in Florida, for example. Rate of transmission is very low here. Among the lowest in the country. It hit mid-90s today. Very humid.
> Also the number of deaths per number of infections keeps going down overall?
Seem to be many protential explanations. Prolly some combo thereof. What is your point?
The vulnerable, under the regime of capo di tuti Cuomo and underboss Bill “the commie” De Blasio, and especially in AOC’s deadly and dingy Congressional district have already been culled.
thanks for the responses. being outside in the open helps anyway so virus spread would be almost non existent in the heat outdoors. but then people are compromising themselves with cool humid air inside buildings. also not helped by ac spreading the virus widely.
but Joshua makes a good point that other states with extensive ac do not have these spikes.
so that is why I feel a thorough study on heat and the virus would be useful before we edge into autumn
tonyb
Humidity is thought to reduce transmission of SARS-CoV-2, not increase it. So, at constant relative humidity, higher temperatures should reduce transmission.
nic
thanks for this but surely we should be beyond the point of ‘thought’ and into the realm of scientific study as heat and humidity are often cited as crucial to virus spread.
For example, as we approach autumn should we try to ensure our homes here in the UK are kept warm with a high humidity or cool and with a low humidity or any combination thereof?
we live by the sea and generally have high humidity and down here in Devon we have had very little virus and no deaths, touch wood, for six weeks. Coincidence?
that is until the hordes denied spain descend on us looking for a holiday. visitors here seem to have no concept whatsoever of social distancing and could create problems for us in the coming weeks. They often seem to be in large groups and presumably think that when on holiday they acquire immunity as nothing nasty can happen to them
tonyb.
“Yes, it would be good to get an expert opinion on why deaths in hot states”
It’s the time of year. Seasonal respiratory diseases follow a particular pattern. The Northern areas have a left skewed peak early in the year and a slow tail. The areas nearer the equator have a more normal curve shape over the middle of the year and Southerm Hemisphere areas get a left skewed peak and a slow tail later in the year.
Again this is all well understood and well documented for other respiratory illnesses.
NeilW – “Yes, it would be good to get an expert opinion on why deaths in hot states”
It’s the time of year. Seasonal respiratory diseases follow a particular pattern. The Northern areas have a left skewed peak early in the year and a slow tail. The areas nearer the equator have a more normal curve shape over the middle of the year and Southerm Hemisphere areas get a left skewed peak and a slow tail later in the year.
Again this is all well understood and well documented for other respiratory illnesses.”
Neil – interesting point -do you have any citation/link etc regarding the differing seasonal peaks of virus based on locations. We currently are having surges/peaks in the southern states which seem counter intuitive to me. While this may be common knowledge among infectious disease experts, it is generally unknown to the general public.
Further insights would be helpful.
Joe –
What does your level of intuition tell you about possible changes in the rate of spread when people go from less public interaction in places like bars to more public interaction in places like bars?
The daddy of them all is apparently
The Transmission of Epidemic Influenza – R Edgar Hope-Simpson (Figure 8.4).
https://link.springer.com/book/10.1007/978-1-4899-2385-1
There’s much more recent seasonal data with greater granularity if you search for data by latitude.
There’s lots of speculation as to reasons for this sort of pattern, but not a lot of conclusions.
What’s increasingly clear is that Covid is likely seasonal too, and that will vary where you are on the planet. Hence why Brazil is blowing up now, but didn’t previously.
Neil –
Comparing to the flu, as a respiratory disease, is of limited utility:
For example:
https://www.statnews.com/2020/06/26/from-nose-to-toe-covid19-virus-attacks-like-no-other-respiratory-infection/
Although the comparison is more apt with respect to infectiousness vs. health impact
Southern states also don’t have the UV variability and length of day variation.
In AZ, it’s barely bearable to be outside a lot of the day. People are choosing to eat indoors.
In northern states, after being shut in, I think people tend to try to spend much more time outside.
Bear in mind that total cases in Florida and Texas are still vastly lower than in New York. Deaths per capita are also 5-10 times lower. But Florida did such a terrible job compared to saint Andrew according to the corrupt media. Florida dnd Texas have more uninfected people left. I have also hard the speculation about hot weather and air conditioning.
> Bear in mind that total cases in Florida and Texas are still vastly lower than in New York.
LOL. Yeah. Bear that in mind: vastly lower
Worldometers:
New York 440,472
Florida 432,747
Texas 404,179
Check back in two days for Florida, maybe two weeks for Texas.
Joshaua – Florida and Texas both have much larger populations than NY . You should use cases per million it will show
cases per million
Texas 14k
NY 22K
Fl 20k
Deaths per million
Texas
NY 1681
Fl 276
Tx 181
Since you are using Worldometers, you should have noticed the columns for deaths per million & Cases per million.
Joe –
I responded to the aspect of David’s statement which was respect to absolute numbers, and which was ridiculously wrong.
Florida may well catch NY even in cases per capita, and perhaps neither will be “vastly lower” in cases per capita by the time it’s all over .
Indeed, in deaths per capita in NY are “vastly” higher.
Lots of complicated reasons for that, including errors by politicians.
What’s intersting to me w/r/t deaths per capita is that some people elude most of those complicated reasons, and are very selective in how they deal with that ratio so as to reinforce political ideology.
For example, some people want to focus on the decisions and leadership of Cuomo in association with deaths per capita in NY, but rationalize away the associations between the deaths per capita in NY, and in the US overall, and the decisions and leadership of Trump.
Joshua –
You said you were responding to david (DPY6629?) absolute numbers that were ridiculously wrong. With the exception of DPY ‘s apparent omitting of “per capita” which is mentioned through the rest of his comment, it is spot on.
Additionally, You throw Trump into the conversation for no reason. It shows you have a strong political bias which is not healthy. There is very little that can be done at the presidential level to make things better or make things worse, It wouldnt have made any difference whether Trump or Hillary or obama been in office when this thing hit. Though the travel ban could have been imposed earlier, but the dems opposed that option.
No question, the CDC screwed up and is part of the trump administration, But the head of CDC, Fauci, and the other experts have been in place for several adminstrations. No president can personally supervise every employee and someone making $200k shouldnt need supervision.
Lets keep politics out of the discussion
Joe –
>Additionally, You throw Trump into the conversation for no reason.
Lol. No reason. We’re discussing the mortality rate in various regions and the relationship to political decisions is irrelevant? Fantastic.
> It shows you have a strong political bias which is not healthy.
I appreciate your concern for my health.
> There is very little that can be done at the presidential level to make things better or make things worse,
Actually, there’s a long list. He could start by not lying about our testing capacity in this country. He could continue by not downplaying the severity of the disease. He could further continue by holding members of his administration accountable and replacing them if they fail in accountability.
It’s really fascinating how much people just can’t accept his fallibilty.
It really is cult-like.
> It wouldnt have made any difference whether Trump or Hillary or obama been in office when this thing hit.
Well, that’s not what he says. He repeats over and over that his decisive actions saved millions of lives (I think how his count is up to 5 million).
I wouldn’t have expected any administration to have been perfect, and there certainly is a wide uncertainty band for assessing the counterfactual of what the results would have been with a different executive in the Oval Office – but his administration has made mistakes. Obvious mistakes. The testing is the biggest one. Despite his lying on the topic, testing has been a fiasco in this country. Would it have been better with another president?
I have no idea – but that doesn’t change the simple fact that it’s been a disaster under his administration.
Again, the cult behaviors are remarkable.
> Though the travel ban could have been imposed earlier, but the dems opposed that option.
Most evidence on the strains indicate that despite his claims, the ” China travel ban” (which was ineffectively implemented, as was the European travel ban) had a marginal effect.
> No question, the CDC screwed up
Under his administration. Fascinating the people who support Mr. “I alone can fix it” give him a free pass on the functioning of his administration.
> But the head of CDC, Fauci…
Fauci is the head of the CDC now? I didn’t know that.
> and the other experts…
Interesting that Trump can get praise for not falling into the trap of the experts, and yet be excused for following the advice of experts, at that same time, form cult mebers.
>Lets keep politics out of the discussion
Perhaps you’re new here. First of all, politics is inextricably linked to the discussions in these pages. More to the point right here, David is constantly focused on the politics – no doubt tens of comments focusing on Cuomo and the fatality rate in New York.
Joe –
> But the head of CDC, Fauci,
Apology. I misread that to think that you were saying that Fauci is the head of the CDC….
My bad.
Of course testing in Florida and Texas testing is vastly more extensive than in New York. Actual infections would track deaths meaning that by any meaningful measure New York is 5 – 10 times worse per capita. Joshua typically can’t acknowledge any truth but nitpicks with largely meaningless statistics. He never sees the point so why would anyone expect him to behave like an adult.
> Of course testing in Florida and Texas testing is vastly more extensive than in New York.
LOL.
Tests per million:
NY: 289,000
Florida: 162,000
Texas: 128,000
Joshua is unaware that Donald Trump is the president of both Texas (181 deaths per million) and New York (1,681 deaths per million) but Andrew Cuomo is governor of only New York.
Which means that except for a handful of densely populated cities that nobody could “lock down” – especially not for a highly contagious virus that has been active in the US since January, 2.5 months before the first lockdown – the US managed the virus better than most of the western world.
Joe –
As you defend David’s grasp of and approach to the numbers, keep in mind that about a week ago he was posting in this thread that the epidemic is over. Let’s hope that the 1400 deaths in this country are the peak, but even if they aren’t or even if they are, keep in mind you’re defending someone who takes that approach to looking at the numbers.
The flattening out of the increase in daily cases is hopefully a good sign. Presumably will find out in 2 or 3 weeks (since we’re already well into the rise in deaths that parallel the beginning of the rise in cases we might expect the flattening in deaths in less than 3 to 4 weeks from today), and hopefully something else will come through and we won’t have any continued rise in delay deaths from yesterday forward. Seems like the fed gov has been banking on magic all along. Maybe it will come through.
This all sounds very intellectual but it’s rather distant from the outcomes we want. Sure, we want this virus to go away. But viruses have always been with us. What we want is this virus, and the next one, and the next novel coronavirus one after, to do less harm, to move through slowly, and to not overwhelm health care capacity. Making hand-washing compulsory at airports seems like a good idea to me, and the correlation between the death rate and housing overcrowding rates ( not density, important distinction ) but overcrowded living conditions is appallingly close to 1.
There is some speculation that the reason the virus has spread much more slowly in the various asian countries, Japan, S Korea, formosa, etc is that they developed cross immunity from previous variations of corona viruses. As opposed to the widely attributed virtues of mask wearing and cultural differences.
Joe –
> As opposed to the widely attributed virtues of mask wearing and cultural differences.
Why the either/or framing?
Additionally, perhaps there might be a few other influential factors as well? As an official non-epidemiologist, what do you think about the possibility that having a competent federal government may have played a role in those countries? For example, conducting rigorous testing and creating a robust infrastructure for contact tracing and isolating?
Just thinking aloud, but maybe their experience with previous epidemics may have taught the a thing or two.
Here’s another speculation:
“MUTATED COVID-19 VIRAL STRAIN IN U.S. AND EUROPE 10 TIMES MORE CONTAGIOUS THAN ORIGINAL STRAIN”
Published: Jun 30, 2020 By Mark Terry in Biospace at https://www.biospace.com/article/mutated-covid-19-viral-strain-in-us-and-europe-much-more-contagious/
“Researchers have been analyzing and tracking the novel coronavirus, SARS-CoV-2, since it first appeared in China in January. Researchers at The Scripps Research Institute have found that the strains spreading so quickly in Europe and the U.S. have a mutated S “spike” protein that makes it about 10 times more infectious than the strain that originally was identified in Asia. The research was published online on bioRxiv at https://www.biorxiv.org/content/10.1101/2020.06.12.148726v1.full.pdf and has yet to be peer-reviewed.”
The National Review comments, “If it seems like the United States is having a tougher time controlling the spread of the coronavirus than Asian countries did in winter and early spring, that’s partially because this version of the virus is tougher to stop from spreading.” https://www.nationalreview.com/2020/07/four-assumptions-about-the-coronavirus/
This explains to me why the lockdowns and contact tracing that worked in East Asia and Australasia will not work in America or Europe, or will not work as well. Nevertheless, Tedros, head of WHO, is still saying he is certain they will work. (They did work, apparently, in Germany.)
NR continues: “The country enacted unprecedented, sweeping lockdowns that kept most Americans at home, at great cost to the economy. These lockdowns slowed the spread of the virus, but did not stop it. … [I]t’s important to recognize that no one is ignoring any simple or easy solutions, because such solutions don’t exist.”
However, in a subsequent article, at https://www.nationalreview.com/corner/coronavirus-update-a-closer-look-at-the-recent-surge/:, NR concedes: “The promotion of mask-wearing and social distancing, and the increased focus on nursing homes, all could make a difference for the better.”
Roger Knights: The Zhang paper you cited says:
“The G614 genotype was not detected in February (among 33 sequences) and observed at low frequency in March (26%), but increased rapidly by April (65%) and May (70%) (Fig. 1b), indicating a transmission advantage over viruses with D614.”
The average period between infection and transmission is about 1 week. Let’s consider an environment where the pandemic with the original strain has stabilized and each infected person on the average infects one new person. Now we introduce the G614 strain which supposedly will be passed on by each infected person to 10 new people. Every week the relative fraction infected with the G614 strain would increase by a factor of 10. In the 10 weeks between March and May, there would be 10^8 more people infected with the G614 than the original D614. However that is not what the data shows. If G614 were 10% more infectious, then the ratio of G614 to D614 would double (1.1^8 = 2.1) after eight cycles of infection followed by transmission. By today, the ratio would increase by a factor of 6.7 (1.1^20). So the advantage is probably closer to 10% than 1000%.
In their experiments with a safe MODEL virus modified to express the SARS-CoV-2 spike protein (a pseudovirus), the G614 mutant did grow 9 fold faster. However, the real SARS-CoV-2 obvious behaves differently.
(Don’t trust liberal or conservative media to accurately convey the results in research papers. Read for yourself.)
Thanks Nic. Encouraging to see such rapid progression to herd immunity.
Any thoughts on how effective treatment impact the results? Might prophylactic use of hydroxychloroquine delay achieving herd immunity?
Or does heterogeneity dominate?
To treat those who do catch Covid19, the Zelenko Protocol achieved 84% lower hospitalizations & 80% lower fatalities (0.79%) by rapid early use of Hydroxychloroquine, Azithromycin & Zinc within 4 days. ~75% of 62 papers on the effectiveness of hydroxychloroquine affirm the effectiveness of rapid early use preferably within 2 days. Conversely, late use in ICU is marginal / inconclusive.
Switzerland was treating with hydroxychloroquine, stopped for 2 weeks, and then resumed. Switzerland’s Covid19 rate correspondingly jumped from 2.4% to 11.5% and back down to 3.0%. There was a similar jump in France. Sources: TheZelenkoProtocol.com, c19study.com and http://www.francesoir.fr/societe-sante/covid-19-hydroxychloroquine-works-irrefutable-proof
David
If prophylactic use of hydroxychloroquine reduces transmission (by reducing infections, not just disease severity once infected) then it would reduce the herd immunity threshold (so long as it continued in widespread use), by reducing the reproduction number. It would also slow progress towards the HIT, so that despite being lower it would be reached later.
If the reduced HIT were overshot (which it is bound to be, to an extent), so that cumulative infections also exceeded the HIT in the absence of prophylactic use of hydroxychloroquine, then the epidemic would not rebound when people ceased such use.
For me, the issue of air conditioning is misapplied; the focus namely at temperature. In a closed environment that happens to be air condition to provide cooling, the airborne organism, ie, the novel coronavirus is recirculated and, when inhaled or impacts the eyes or nose, become infectious. Unless the air filtration system scrubs the air of micro organisms, even a “HEPA” system, then the indoor environment along with air conditioning is a mass contamination system. We can go back to “Typhoid Mary” and her contaminating the water supply until the pump handle was removed. For indoor air decontamination of this airborne virus, most indoor environments will have to install air handling equipment capable of reducing substantially the airborne virus load. The systems exist, the costs are high, the efficacy variable if other pollutants like cigarettes smoke clogs the system. Ban smoking. Have high flow air handling systems being filtered by constantly cleansed systems, and voila, you can return to indoor dining sans face masks.
Open some windows and run the A/C. The energy conservation sealing has some downsides.
Reblogged this on Climate Collections.
If mere exposure to colds in general provided resistance to get covid-19 infection, I would think infection rates in an urban metropolis like NYC would be less for covid-19 than it has been in as much as they probably have been exposed to cold viruses in general to a greater extent than less crowded areas over the years…
“A key reason for variability in susceptibility to COVID-19 given exposure to the SARS-CoV-2 virus causing is that the immune systems of a substantial proportion (35% to 80%) of unexposed individuals have T-cells, circulating antibodies or other components that are cross-reactive to SARS-CoV-2 and can be expected to provide substantial resistance to it.[6] [7] [8] [9] Such components likely arise from past exposure to common cold or other coronaviruses, or to influenza.[10] Not being specific to SARS-CoV-2, and typically not being antibodies, such immune system components are not normally detected in seroprevalence or other tests for immunity to SARS-CoV-2.”
–
Much and all as I like the gist of this article I feel the above statement does not gel.
Medically speaking you either have antibodies to the disease or you do not.
The reasons why a virus does not affect everyone in its outbreak or spread is complex. A bad flu season might only affect 5% of the population in any one year. Why so low?
There are a lot of factors you allude to, basically a group of people who are more social or more vulnerable, there is the time of year of the outbreak as seasonal factors affect viral viability. These are the dynamics in play. Exposure and viral load are critical
–
Some cases in point.
Heavy exposure to the virus, as seen in Italy and Wuhan in doctors and nurses resulted virtually 100% infection as expected. These are people whose workloads dictate exposure to more colds, flus etc and higher T-cell stimulation and development and yet they all still caught it. According to that part of the theory put forward there would be a large cohort of people who should be “naturally” immune.
Sorry, it is just not so.
-35-80% sounds like an estimate of ECS, so broad it is meaningless.
Multiple different unprovable contributing factors puts the fudge on top.
–
HIT is not a fixed number, the threshold varies seasonally and with the specifics of the infecting agent. The troubling fact that young children find it hard to catch shows that for this virus the other factor is the presence of ACE 2 receptors ? meaning that the load of virus needed to infect could vary with how many receptors you have ( more as you get older).
This may be much more important than speculation about T cells which does not transfer from the Petrie Dish to real life
angtech
May I suggest that you read the papers that I cited, and others concerning T-cells and COVID-19.
I didn’t say that cross-reactive T-cells etc. provided immunity, just “substantial resistance”. T-cell defences may not technically prevent infection, but they disrupt virus replication and so prevent disease or reduce its severity. Very high viral doses may well overcome T-cell defences, which could explain why infection rates in doctors and nurses, working in enclosed spaces and at close quarters to infected people, can be very high.
COVID-19 infections in healthcare workers are not uniformly high. for instance, in a large referral hospital in Barcelona, Spain the prevalence in April of SARS-CoV-2 infection was 11.2% (https://doi.org/10.1101/2020.04.27.20082289). You provide no source for your “virtually 100% infection” assertion.
niclewis
Thank you for your courtesy in addressing my comments.
I should have added that I enjoy your writing and research.
“May I suggest that you read the papers that I cited, and others concerning T-cells and COVID-19.”
I do have some knowledge of the subject. One of my close acquaintances worked in the early T cell research in the 1974-76 era at Monash University in Victoria, Alfred Hospital.
–
“I didn’t say that cross-reactive T-cells etc. provided immunity, just “substantial resistance”.
–
True, the implication is that a substantial number of people can be immune to the virus without going down the traditional route of developing antibodies [exposure].
–
“A key reason for variability in susceptibility to COVID-19 given exposure to the SARS-CoV-2 virus causing is that the immune systems of a substantial proportion (35% to 80%) of unexposed individuals have T-cells, circulating antibodies or other components that are cross-reactive to SARS-CoV-2 and can be expected to provide substantial resistance to it.[6] [7] [8] [9] Such components likely arise from past exposure to common cold or other coronaviruses, or to influenza.[10] Not being specific to SARS-CoV-2, and typically not being antibodies, such immune system components are not normally detected in seroprevalence or other tests for immunity to SARS-CoV-2.”
–
Medically some people have resistance to infections even without prior exposure to any of the causes mentioned. Some people never catch the Flu, for instance. Nonetheless these are not key reasons for the variability in susceptibility.
–
“You provide no source for your “virtually 100% infection” assertion.”
–
True. My comment was ‘ Heavy exposure to the virus, as seen in Italy and Wuhan in doctors and nurses “. Do you dispute heavy exposure causing virtually 100% infection unlikely?
“The minimal infective dose is defined as the lowest number of viral particles that cause an infection in 50% of individuals”. It can only logically go up from there
“Comment
Published: 07 July 2020
Pre-existing immunity to SARS-CoV-2: the knowns and unknowns
Alessandro Sette & Shane Crotty
Nature Reviews Immunology volume 20, pages457–458(2020)Cite this article
113k Accesses
2527 Altmetric
Metricsdetails
T cell reactivity against SARS-CoV-2 was observed in unexposed people; however, the source and clinical relevance of the reactivity remains unknown. It is speculated that this reflects T cell memory to circulating ‘common cold’ coronaviruses. It will be important to define specificities of these T cells and assess their association with COVID-19 disease severity and vaccine responses.
As data start to accumulate on the detection and characterization of SARS-CoV-2 T cell responses in humans, a surprising finding has been reported: lymphocytes from 20–50% of unexposed donors display significant reactivity to SARS-CoV-2 antigen peptide pools1,2,3,4.
In a study by Grifoni et al.1, reactivity was detected in 50% of donor blood samples obtained in the USA between 2015 and 2018, before SARS-CoV-2 appeared in the human population. T cell reactivity was highest against proteins other than the coronavirus spike protein, but T cell reactivity was also detected against spike. The SARS-CoV-2 T cell reactivity was mostly associated with CD4+ T cells, with a smaller contribution by CD8+ T cells1. Similarly, in a study of blood donors in the Netherlands, Weiskopf et al.2 detected CD4+ T cell reactivity against SARS-CoV-2 spike peptides in 1 of 10 unexposed subjects and against SARS-CoV-2 non-spike peptides in 2 of 10 unexposed subjects. CD8+ T cell reactivity was observed in 1 of 10 unexposed donors. In a third study, from Germany, Braun et al.3 reported positive T cell responses against spike peptides in 34% of SARS-CoV-2 seronegative healthy donors (CD4+ and CD8+ T cells were not distinguished). Finally, a study of individuals in Singapore, by Le Bert et al.4, reported T cell responses to nucleocapsid protein nsp7 or nsp13 in 50% of subjects with no history of SARS, COVID-19, or contact with patients with SARS or COVID-19. A study by Meckiff using samples from the UK also detected reactivity in unexposed subjects5. Taken together, five studies report evidence of pre-existing T cells that recognize SARS-CoV-2 in a significant fraction of people from diverse geographical locations.
These early reports demonstrate that substantial T cell reactivity exists in many unexposed people; nevertheless, data have not yet demonstrated the source of the T cells or whether they are memory T cells. It has been speculated that the SARS-CoV-2-specific T cells in unexposed individuals might originate from memory T cells derived from exposure to ‘common cold’ coronaviruses (CCCs), such as HCoV-OC43, HCoV-HKU1, HCoV-NL63 and HCoV-229E, which widely circulate in the human population and are responsible for mild self-limiting respiratory symptoms. More than 90% of the human population is seropositive for at least three of the CCCs6. Thiel and colleagues3 reported that the T cell reactivity was highest against a pool of SARS-CoV-2 spike peptides that had higher homology to CCCs, but the difference was not significant.
What are the implications of these observations? The potential for pre-existing crossreactivity against COVID-19 in a fraction of the human population has led to extensive speculation. Pre-existing T cell immunity to SARS-CoV-2 could be relevant because it could influence COVID-19 disease severity. It is plausible that people with a high level of pre-existing memory CD4+ T cells that recognize SARS-CoV-2 could mount a faster and stronger immune response upon exposure to SARS-CoV-2 and thereby limit disease severity. Memory T follicular helper (TFH) CD4+ T cells could potentially facilitate an increased and more rapid neutralizing antibody response against SARS-CoV-2. Memory CD4+ and CD8+ T cells might also facilitate direct antiviral immunity in the lungs and nasopharynx early after exposure, in keeping with our understanding of antiviral CD4+ T cells in lungs against the related SARS-CoV7 and our general understanding of the value of memory CD8+ T cells in protection from viral infections. Large studies in which pre-existing immunity is measured and correlated with prospective infection and disease severity could address the possible role of pre-existing T cell memory against SARS-CoV-2.
If the pre-existing T cell immunity is related to CCC exposure, it will become important to better understand the patterns of CCC exposure in space and time. It is well established that the four main CCCs are cyclical in their prevalence, following multiyear cycles, which can differ across geographical locations8. This leads to the speculative hypothesis that differences in CCC geo-distribution might correlate with burden of COVID-19 disease severity. Furthermore, highly speculative hypotheses related to pre-existing memory T cells can be proposed regarding COVID-19 and age. Children are less susceptible to COVID-19 clinical symptoms. Older people are much more susceptible to fatal COVID-19. The reasons for both are unclear. The age distribution of CCC infections is not well established and CCC immunity should be examined in greater detail. These considerations underline how multiple variables may be involved in potential pre-existing partial immunity to COVID-19 and multiple hypotheses are worthy of further exploration, but caution should be exercised to avoid overgeneralizations or conclusions in the absence of data.
Pre-existing CD4+ T cell memory could also influence vaccination outcomes, leading to a faster or better immune response, particularly the development of neutralizing antibodies, which generally depend on T cell help. At the same time, pre-existing T cell memory could also act as a confounding factor, especially in relatively small phase I vaccine trials. For example, if subjects with pre-existing reactivity were assorted unevenly in different vaccine dose groups, this might lead to erroneous conclusions. Obviously, this could be avoided by considering pre-existing immunity as a variable to be considered in trial design. Thus, we recommend measuring pre-existing immunity in all COVID-19 vaccine phase I clinical trials. Of note, such experiments would also offer an exciting opportunity to ascertain the potential biological significance of pre-existing SARS-CoV-2-reactive T cells.
It is frequently assumed that pre-existing T cell memory against SARS-CoV-2 might be either beneficial or irrelevant. However, there is also the possibility that pre-existing immunity might actually be detrimental, through mechanisms such as ‘original antigenic sin’ (the propensity to elicit potentially inferior immune responses owing to pre-existing immune memory to a related pathogen), or through antibody-mediated disease enhancement. While there is no direct evidence to support these outcomes, they must be considered. A detrimental effect linked to pre-existing immunity is eminently testable and would be revealed by the same COVID-19 cohort and vaccine studies proposed above.
There is substantial data from the influenza literature indicating that pre-existing cross-reactive T cell immunity can be beneficial. In the case of the H1N1 influenza pandemic of 2009, it was noted that an unusual ‘V’-shaped age distribution curve existed for disease severity, with older people faring better than younger adults. This correlated with the circulation of a different H1N1 strain in the human population decades earlier, which presumably generated pre-existing immunity in people old enough to have been exposed to it. This was verified by showing that pre-existing immunity against H1N1 existed in the general human population9,10. It should be noted that if some degree of pre-existing immunity against SARS-CoV-2 exists in the general population, this could also influence epidemiological modelling, and suggests that a sliding scale model of COVID-19 susceptibility may be considered.
In conclusion, it is now established that SARS-CoV-2 pre-existing immune reactivity exists to some degree in the general population. It is hypothesized, but not yet proven, that this might be due to immunity to CCCs. This might have implications for COVID-19 disease severity, herd immunity and vaccine development, which still await to be addressed with actual data.”
Actual data, go figure
with regard to CD4+ function. In deep profiling of patients with Covid,
https://science.sciencemag.org/content/sci/early/2020/07/15/science.abc8511.full.pdf
Three different classes of immunology types were identified.
eye opening
Re: “May I suggest that you read the papers that I cited, and others concerning T-cells and COVID-19.
I didn’t say that cross-reactive T-cells etc. provided immunity, just “substantial resistance”. T-cell defences may not technically prevent infection, but they disrupt virus replication and so prevent disease or reduce its severity”
As I, other immunologists, vaccine scientists, epidemiologists, etc. pointed out for months, cross-reactivity (including cross-reactive T cells) does not necessarily entail a benefit, let alone does it entail cross-reactive T cells limiting SARS-CoV-2 infection rates. Studies on TCR binding to viral peptides on MHC molecules, BCR binding to viral epitopes, B cells making antibodies that bind to both SARS-CoV-2 and other coronaviruses, etc., tells you that an immune response occurs. They don’t tell you whether that response is beneficial, especially for a virus like SARS-CoV-2 that causes immune dysregulation with cytokine storm in COVID-19, engages in immunoevasion, is much more virulent than numerous other coronaviruses (such as those that cause colds), is more contagious with a larger R0 than a number of other viruses such as seasonal influenza viruses, etc.
Moreover, it’s not even clear that the cross-reactive immune response from prior exposure to other coronaviruses would be as good as, or better than, the initial phase of the adaptive antigen-specific (B and T cell) response that’s already present even in the absence of prior coronavirus infection. Same for being as good as, or better than, the innate immune response (ex: macrophages, dendritic cells, NK cells, etc.) that’s already present without need for prior infection. Even now, the published evidence has not shown a benefit from cross-reactivity in the adaptive immune response to SARS-CoV-2:
http://archive.is/ISw5W#selection-20053.0-20330.0
https://twitter.com/profshanecrotty/status/1293346418158051330
co-author of:
“Pre-existing immunity to SARS-CoV-2: the knowns and unknowns
[…]
It is frequently assumed that pre-existing T cell memory against SARS-CoV-2 might be either beneficial or irrelevant. However, there is also the possibility that pre-existing immunity might actually be detrimental, through mechanisms such as ‘original antigenic sin’ (the propensity to elicit potentially inferior immune responses owing to pre-existing immune memory to a related pathogen), or through antibody-mediated disease enhancement. While there is no direct evidence to support these outcomes, they must be considered. A detrimental effect linked to pre-existing immunity is eminently testable and would be revealed by the same COVID-19 cohort and vaccine studies proposed above.”
https://www.nature.com/articles/s41577-020-0389-z
and of:
“Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals
[…]
There is also great uncertainty about whether adaptive immune responses to SARS-CoV-2 are protective or pathogenic, or whether both scenarios can occur depending on timing, composition, or magnitude of the adaptive immune response.”
https://www.sciencedirect.com/science/article/pii/S0092867420306103
“Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients”
“The potential danger of suboptimal antibody responses in COVID-19”
“A plea for the pathogenic role of immune complexes in severe COVID-19”
“Antibody dependent enhancement due to original antigenic sin and the development of SARS”
Working paper: “Paradoxical dynamics of SARS-CoV-2 by herd immunity and antibody-dependent enhancement”
“Dengue fever, COVID‐19 (SARS‐CoV‐2), and antibody‐dependent enhancement (ADE): A perspective”
Detrimental cross-reactivity in the context of other viral conditions:
“Immunity to dengue virus: a tale of original antigenic sin and tropical cytokine storms“
“Original antigenic sin impairs cytotoxic T lymphocyte responses to viruses bearing variant epitopes”
“The role of T cell antagonism and original antigenic sin in genetic immunization”
So once again: Nic Lewis has no expertise in immunology, epidemiology, or any biology topic pertinent to COVID-19. And Judith Curry largely protects him from criticism by often blocking comments that shows he’s wrong. This website has become another haven for right-wing, politically-motivated COVID-19 disinformation (as it previously was on climate science), whether it’s:
1) peddling the conspiracy theory that SARS-CoV-2 originally came from a lab in Wuhan
2) repeatedly under-estimating SARS-CoV-2’s infection fatality rate
3) taking advantage of right-censoring to under-estimate COVID-19 deaths on the Diamond Princess
4) under-estimating the proportion of people SARS-CoV-2 can infect [ex: by distorting cross-reactivity to under-estimate the herd immunity threshold]
5) concealing how much larger Sweden’s COVID-19’s deaths per capita are than nearby countries that locked down
6) acting as if hydroxychloroquine works for COVID-19 / SARS-Cov-2 infection, long after it was shown not to
And so on, dating back to at least late April.
There’s a reason why (with the exception of Joshua, mosher, verytallguy, and maybe a couple of others) virtually no one with any substantial understanding of COVID-19 comes here or comments here. There’s a reason why Lewis or Curry aren’t publicly running their COVID-19 claims by domain experts. So I’ll leave folks to this right-wing echo chamber they’ve chosen, away from informed experts who easily debunk the non-expert distortions Lewis peddles.
https://twitter.com/AtomsksSanakan/status/891040491214688257
https://medium.com/@silentn2040/the-dangerous-myth-that-sweden-achieved-herd-immunity-fd2579526b8b
For the record, the comment by Atomsk’s Sanakan contain multiple false, baseless and/or misleading claims. Examples (text from the comment is in quotes) are:
“Nic Lewis has no expertise in immunology, epidemiology, or any biology topic pertinent to COVID-19. And Judith Curry largely protects him from criticism by often blocking comments that shows he’s wrong.”
– I’ll leave other, less partisan, individuals to judge whther I have sufficient expertise in epidemiological modeling relating to COVID-19 to write about this subject.
– the claim about Judith Curry is false. She appears to have blocked hardly any comments.
“1) peddling the conspiracy theory that SARS-CoV-2 originally came from a lab in Wuhan”
– this theory is not something I’ve posted on, but it’s not correct to describe it as a ‘conspiracy theory’. Some experts consider the theory to be plausible, given the available evidence. It seems unlikely that the theory will be either proved or disproved.
“2) repeatedly under-estimating SARS-CoV-2’s infection fatality rate”
– this is an unspecific and unsubstantiated claim. I am unaware of any evidence supporting it.
“3) taking advantage of right-censoring to under-estimate COVID-19 deaths on the Diamond Princess”
– that is an outright falsehood. In my article that used deaths data from the Diamond Princess, I allowed for right-censoring, using the original authors’ death rate model. I wrote ‘As at 21 March the Verity et al. model estimates that 96% of the eventual deaths should have occurred, so we can scale up to 100%’. As it subsequently turned out, the Verity et al. death model underestimated the final number of deaths, but I wasn’t to know that would be the case.
“4) under-estimating the proportion of people SARS-CoV-2 can infect [ex: by distorting cross-reactivity to under-estimate the herd immunity threshold]”
– my estimates of the HIT have generally been in the same ballpark as those in the published Gomes et al, Aguas et al. and Tkachenko et al. studies.
– my original article didn’t even mention cross-reactivity.
– heterogeneity in biological susceptibility is in any event not the most important cause of the HIT being lower in my and the aforementioned other published analyses than it would be for a homogeneous population.
“5) concealing how much larger Sweden’s COVID-19’s deaths per capita are than nearby countries that locked down”
– how can I have ‘concealed’ information when it is readily accessible, and frequently publicised by proponents of lockdowns?
“As an immunologist, I can say what you just wrote makes no sense and has been repeatedly debunked in the scientific literature.”
The link given for this statement is from a twitter thread in which Atomsk’s Sanakan said this in response to a tweet from ‘Christina’ which read
‘The Aluminum,Thiomersal, Poly-sorbet 80 & whatever garbage kills our gut bacteria-This causes a cytokine storm=/causes brain damage/swelling’
This has nothing whatsoever to do with any post at Climate Etc.
I note that Atomsk’s Sanakan claims to be an immunologist. While I have no reason to doubt this assertion, as he hides his identity it is not possible to verify it.
Atomsk’s Sanakan, quoting Shane Crotty: but fewer would become severely ill and die from COVID-19.
That seems to be worth more emphasis than you have given it.
Atomsk’s Sanakan: 6) acting as if hydroxychloroquine works for COVID-19 / SARS-Cov-2 infection, long after it was shown not to
This topic has been much disputed, not promoted by everyone here. Dr Didier Raoult’s latest detailed report is mildly supportive.
I’ll repost here:
More details on clinical practice in Didier Raoult practice in Marseille:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315163/
matthewrmarler | August 10, 2020 at 11:50 am | Reply
a snippet: Considering that death was a main outcome and that only 35 patients died in our cohort (0.9%), the number of covariates to be included in multivariate analyses was a priori limited to three variables: previous health status (modified Charlson combined comorbidity index) [22], severity of the disease (NEWS-2 score) and treatment (HCQ-AZ for at least 3 days).Association between treatment (HCQ + AZ≥3days) and death was estimated by Cox regression models using three different methods. In the primary analysis, a multivariable Cox regression adjusted on the combined comorbidity index and the NEWS score was performed. We conducted a secondary analysis that used propensity-score matching. The propensity score was calculated using multivariable logistic regression on the combined comorbidity index and the NEWS score. Each patient of the “other treatment” group was matched to a patient selected of the “HCQ-AZ ≥ 3 days” group using the 1:1 nearest-neighbour propensity score matching method to create a matched sample. The third analysis used inverse probability weighting
matthewrmarler | August 10, 2020 at 2:47 pm |
to me, this is the strongest evidence yet published in support of early use of HCQ. Table two shows clearly that the “best treatment” group was not exactly matched by the other treatment groups on comorbidities or age; the authors attempted to address that with a propensity score analysis. Granted that such things can’t be done perfectly, it looks to be like they did it well (also, I well remember being totally fooled by the Lancet study that was bogus.)
selected results: The mean duration of hospitalization was significantly shorter in the HCQ-AZ group (7.3 days (sd 7) vs 9.2 (sd 8.1) than in the other treatment groups. The proportion of patients hospitalized �10 days was 3.5% in the HCQ-AZ group and 14.2% in the other treatment groups (Table 4). We observed that 9 of the 35 patients who died (25.7%) developed a concurrent bacterial infection, including community-acquired Streptococcus pneumoniae in 2 patients, ventilation-acquired pneumonia in 4 patients, catheter-associated septicaemia in 2 patients and cholecystitisrelated septicaemia in 1 patient (Table S5).
As the youngest patient who died was 60 , …
Reducing hospital stay by 1.9 days on average, on a large number of patients, is a good result, to my mind.
I think that this paper deserves a wide readership.
Very few if any claims are posted at Climate Etc without being disputed.
.
Re: “Atomsk’s Sanakan, quoting Shane Crotty: but fewer would become severely ill and die from COVID-19.
That seems to be worth more emphasis than you have given it.”
You misleadingly left out the rest of the quote, despite it being clearly shown to you. There’s a term for mining quotes in that way:
“Additionally, even if our most optimistic speculations about crossreactive T cell memory were found to be correct, it would mean that just as many people would get infected with SARS-CoV-2, but fewer would become severely ill and die from COVID-19.”
You left out the rest of the quote to make it look like Crotty was saying that fewer would become severely ill and die. Instead he’s saying that would be the case under the most optimistic speculations. But they have not shown yet that those optimistic speculations are true, as per the published work I quoted from him. In that work Crotty explicitly notes that the response could instead be useless or harmless, instead of causing fewer to become severely ill and die. You willfully ignored that, as expected:
“It is frequently assumed that pre-existing T cell memory against SARS-CoV-2 might be either beneficial or irrelevant. However, there is also the possibility that pre-existing immunity might actually be detrimental […].”
https://www.nature.com/articles/s41577-020-0389-z
“There is also great uncertainty about whether adaptive immune responses to SARS-CoV-2 are protective or pathogenic, or whether both scenarios can occur depending on timing, composition, or magnitude of the adaptive immune response.”
https://www.sciencedirect.com/science/article/pii/S0092867420306103
And again, for the same thread in which that quote comes from:
https://twitter.com/profshanecrotty/status/1293346134505660416
I also went over other research on cross-reactivity being detrimental in the immune response to other pathogens, along with T cells often being detrimental to the immune response to SARS-CoV-2. You conveniently ignored those as well, again as expected.
Seriously, Matthew, enough already. It’s this type of thing that made me usually disregard your comments. I’ll now go back to doing so, and Curry can feel free to return to blocking comments to shield you from rebuttals.
Steven Mosher
Yes, I read the Sette et al. paper a few weeks ago. it’s a useful study. As they say, there are many unanswered questions.
Thanks for the link to the Matthew et al Science study, which I had missed.
Given the huge complexity of the human immune system and inter-person differences in genotype and in past environmental exposure to different disease causing agents and other factors, it seems unsurprising that people’s resistance to infection by SARS-CoV-2 will vary widely given the same exposire to it.
Nonetheless, differing social connectivity appears to be the more important factor in lowering the HIT from that applicable in a homogeneous population or for random vaccination.
Steven
Thanks for that extensive research.
N.B.
“ Furthermore, highly speculative hypotheses related to pre-existing memory T cells can be proposed regarding COVID-19 and age. Children are less susceptible to COVID-19 clinical symptoms. Older people are much more susceptible to fatal COVID-19.“
–
The T cells might have some primitive memory, but seem to develop more in response to infections that our bodies process.
The take away idea is that children’s T cells have not developed their responses fully and get more as they grow older.
Therefore children should get COVID 19 more often and more severely than adults, having less innate resources.
This is obviously not true and shows, as I have stated that T cells are not an important active force in a new viral infection such as COVID 19 despite its genetic links to other corona viruses.
The most likely explanation at the moment for children not catching it readily and not getting as ill with it is that the viral attachment or the viral reproduction is stopped or slowed down by lack of a receptor site. ( ? Ace 2 related.
–
A lot of speculative stuff sometimes translates to belief that things must and do happen because of a vague possibility.
Like tipping points.
T cells seem to be more involved in ways like early destruction and mopping up of already infected cells which may result in less virus being produced. This may help develop a quicker antibody production.
Destruction of cells triggers a quicker recognition of and adaption to a viral infection. It might mean the difference between a severe cold and death but is not the way in which the body prevents infection.
angtech
You say “The T cells might have some primitive memory, but seem to develop more in response to infections that our bodies process.
The take away idea is that children’s T cells have not developed their responses fully and get more as they grow older.
Therefore children should get COVID 19 more often and more severely than adults, having less innate resources.
This is obviously not true and shows, as I have stated that T cells are not an important active force in a new viral infection such as COVID 19 despite its genetic links to other corona viruses.”
I’m afraid this is all wrong.
It is hypothetised that children have more cross-reactive T-cells due to their (paricularly young children’s) higher frequency of infection by common-cold coronavirsues, and hence are more resistant to COVID-19 than adults.
But there may well be other reasons why children are both less likely to be infected by SARS-CoV-2 and to develop much less severe disease if infected, than adults.
Nic
“I’m afraid this is all wrong.
It is hypothetised that children have more cross-reactive T-cells due to their (paricularly young children’s) higher frequency of infection by common-cold coronavirsues, and hence are more resistant to COVID-19 than adults.”
–
You cannot get cross reactive T cells until you have been exposed to infections to get the cross reactivity.
Very young children have some immunity to cold viruses from maternal antibodies and the from milk antibodies so they cannot develop cross reactivity.
After 12 months their immune system is robust enough to react efficiently to what comes their way.
All teenagers and older people have gone through this rite of passage and have developed both their antibodies and T cell functions.
Older people should have the most cross reactivity possible, not the least.
The hypothesis that young children can resist covid better is an attempt to make a miracle out of a molehill.
The best way to illustrate the flaw in the logic is simple. Children catch a lot of colds when they go to pre school (4-5years old) or day care (younger). They catch a lot of colds. Covid is a cold virus. How can they be prone to catching all the other cold viruses but mysteriously have a high resistance to just one cold virus, covid. Answer, they don’t.
As they get older their immunity to cold viruses is because of the antibodies they develop, not the T cells per se.
–
As said this is a minor side issue to the much more important facts you are presenting. Herd immunity is determined by who is infected eg social types etc and how often they are able to pass the infection on.
angtech
As I’ve pointed out before, old people suffer from a less efficient T-cell response – “T-cell exhaustion”.
Most common cold viruses infections have an estimated R_0 value of about 6, considerably higher than for SARS-CoV-2. Moreover they have a much shorter incubation period. Therefore they will spread much more readily than COVID-19 in children (and other parts of the population) for any given average level of resistance.
The level of T-cells resulting from common cold coronaviruses declines with time since infection. As pre-school and younger school children get colds more often, they can be expected to have a higher level of cross-reactive T-cells than teenagers and adults – who as you say will have more developed antibody armouries against common cold coronaviruses.
Beginning of first quarter (very small sample size):
–snip–
The greatest risk of transmission to contacts was found for the 14 cases <15 years of age (22.4%); 8 of the 14, who ranged in age from <1 to 11 years) infected 11 of 49 contacts. Overall, 606 outbreaks were identified, 74% of which consisted of only two cases. Discussion The open-source software program permitted the centralized tracking of contacts and rapid identification of links between cases. Workplace contacts were at higher risk of developing symptoms. Although childhood contacts were less likely to become cases, children were more likely to infect household members, perhaps because of the difficulty of successfully isolating children in household settings.
–snip–
https://www.medrxiv.org/content/10.1101/2020.07.16.20127357v1
Shows why it's just insane that we've failed so badly at contact tracing.
https://mobile.twitter.com/DrZoeHyde/status/1288779767131459587
Nic
76 %
https://www.thedailybeast.com/a-summer-camp-took-almost-every-precaution-the-majority-of-kids-still-got-covid-19
there are many examples of congregate settings where attack rates
are above 50%
I’ve see, 76%, 50%, 80%, and 100%
angech
what Nic ignores is that “reactivity” does not entail Immunity.
1. yes it could provide protection. this is an unknown
2. It could provide NO ADDITIONAL benefit, this is an unknown
3. it could cause HARM ( via over reaction) this is an unknown.
nic doesnt model this separate unknown
further he is wrong about children. 76% attack rate in the most recent
study of campers.
Nic will use NONE of this data to constrain his modelling estimates
so you can basically throw his work out the window.
he will make arguments as to why this data should not inform our understanding rather than using it to constrain or inform our understanding
“The most likely explanation at the moment for children not catching it readily and not getting as ill with it is that the viral attachment or the viral reproduction is stopped or slowed down by lack of a receptor site. ( ? Ace 2 related.”
mere speculation. and wrong
https://www.cdc.gov/mmwr/volumes/69/wr/mm6931e1.htm
“Nonetheless, differing social connectivity appears to be the more important factor in lowering the HIT from that applicable in a homogeneous population or for random vaccination.”
there is no doubt that differing social connectivity plays a role.
but “connectivity” is ambiguous.
Take a church of people who regularly meet and are highly connected
A) make them wear masks
B) allow them to go mask free.
Both groups will have the same “connectivity” but one will exhibit a higher
R[t] because of the differing NPI practice
basically all the data you work from is hopelessly confounded by
A) differing PHYSICAL connectivity ( how many people I mix with)
B) differing practices in regard to NPI
We see it daily here in Korea where we have implemented practices
to change the daily physical contact amongst people. Simply,
Korea has cultural practices that increase prolonged close contact.
A) Norabangs
C) PC cafes
D) daily after work company dinners
When we put a stop to those, the infection rate plummets
When we allow these activities with masks, we get clusters that are directly traceable to the failure to wear masks.
we saw the same thing in China. When china started its policy of quarantining sick family members, the rate of course dropped.
But isolating the sick and asymptomatic early on, does not mean that
HI is achieved at low number. They just changed the mixing dynamics.
Getting to near zero cases is easy to do within 14 days as shown
all across china. residents were allowed to leave their house 1 time
per week. In every city the cases fell. But that did not mean they reached
HI. They just changed mixing dynamics.
The way you have defined HI results in a metric that changes across
the wide variety of human behavior and has no practical meaning as a consequence.
For example: under your definition of HI, we would have achieved
HI here in Korea, If we went back to normal ( people congregating
in church, in PC cafes, returning to the after work company dinners)
AND if R[t] remained below 1, then we would have achieved HI.
What we dont know and are unwilling to do is this:
Test the hypothesis that the current R[t] which is below 1, will REMAIN
below 1 if we return to normal mixing and no mask wearing.
we know how to get it below 1. we stop mixing like we used to. we wear masks. But that’s not HI. Herd immunity is achieved for a community that has an R[t] <1 while engaging in it's normal behavior.
Steven Mosher:
You use South Korea and China as examples. That’s not a choice we will make. We are making our choices now and our state and local governments will fiddle around the edges.
Such a tight control from the above, leaves them like New Zealand. How long will this go on and at what economic costs? Having puppets dance and prove us wrong is nice. We are still the things that made us great.
China is a lab of horrors. It worked worked for them. Good.
You mention HI. Then there’s effective HI. Which includes other stuff. Like not opening schools. What we’re looking for is the Go signal. At low resolution, Lewis has said, that signal is pretty close, and that’s my interpretation, not his. In my opinion, he’s arguing against those that are making themselves the problem.
We got a pretty wide landing zone, we just need to jump out of the plane. We can do this.
–snip–
Our final cohort included 145 patients with mild to moderate illness within 1 week of symptom onset. We compared 3 groups: young children younger than 5 years (n = 46), older children aged 5 to 17 years (n = 51), and adults aged 18 to 65 years (n = 48). We found similar median (interquartile range) CT values for older children (11.1 [6.3-15.7]) and adults (11.0 [6.9-17.5]). However, young children had significantly lower median (interquartile range) CT values (6.5 [4.8-12.0]), indicating that young children have equivalent or more viral nucleic acid in their upper respiratory tract compared with older children and adults (Figure). The observed differences in median CT values between young children and adults approximate a 10-fold to 100-fold greater amount of SARS-CoV-2 in the upper respiratory tract of young children. We performed a sensitivity analysis and observed a similar statistical difference between groups when including those with unknown symptom duration. Additionally, we identified only a very weak correlation between symptom duration and CT in the overall cohort (Spearman ρ = 0.22) and in each subgroup (young children, Spearman ρ = 0.20; older children, Spearman ρ = 0.19; and adults, Spearman ρ = 0.10).
–snip–
https://jamanetwork.com/journals/jamapediatrics/fullarticle/2768952
> Dropping antibody counts aren’t a sign that our immune system is failing against the coronavirus, nor an omen that we can’t develop a viable vaccine.
https://www.nytimes.com/2020/07/31/opinion/coronavirus-antibodies-immunity.html#click=https://t.co/eyUCpliy6H
Steven Mosher:
—————————–
basically all the data you work from is hopelessly confounded by
A) differing PHYSICAL connectivity ( how many people I mix with)
B) differing practices in regard to NPI
—————————–
So when South Korea and China are merged with the above, the data becomes more usable. A) is low, B) is high, and the math spits out, not much to see here. But you’ve just delayed things. Which may have merit. But also has its weaknesses. You do not get the elimination. You get shrinkage while worrying about unrealized potential. You wall yourself off on many scales. It’s like going on a diet. Here’s your report card. Do you feel bad yourself? It’s abusive. The ones that are used to that, no problem. The MSM is fat shaming. And we follow the science and the data.
My level is set at 350,000 deaths. Which translates loosely into a lifespan of 800 years. Which is another goal we should not be pursuing at this time.
So how to account for your two problems above? Full lockdown. Required masks. The math cleans up and simplifies. So that’s math can only be applied to certain countries. We could also do something with our smartphones about tracking. We could even listen in on people to aid with that. Do we want to do these things. If we do these things, is it a form of training?
In the future, we could use this data to counter rioters. The illegal drug trade. We have lots of data. It’s supposed to be locked up now. But only if it fits our point of view.
Joshua: “Shows why it’s just insane that we’ve failed so badly at contact tracing.”
A big part of the problem is that the fast-turnaround tests used in Korea are not allowed here. Without fast-result tests, like the ten-minute test described below, contact tracing is difficult and even pointless.
“Out of the Way, FDA”
[Extracts; I’ve had to omit some valuable paragraphs]
By Robert Zubrin nationalreview.com July 30, 2020
“Benner’s coronavirus test is currently being used in India, a country that, despite having four times America’s population and much more unfavorable living conditions, has one quarter of our coronavirus death toll. But it is not being used in the U.S.A.
With tests such as Benner’s we could test the whole national work force every week, quarantine the infected, release the uninfected, and end the pandemic within two months. Currently 11 percent of the U.S. labor force is unemployed. If 0.5 percent drawn from those out of work were hired to test all 100 percent of the workforce, they would only have to each test 40 people per day in order to test everyone every 5 days. The cost would be substantial in absolute terms, but trivial compared with what we are now shelling out in relief payments, economic dislocation, medical bills, suffering, and deaths.
There is only one thing stopping such an effective program from being implemented, whether at the federal, state, local, company, or individual level. That is the obstinacy of the FDA.
Obtaining FDA approval is impossible for an innovative small biotech company such as Firebird with limited capital. The Firebird test was easily proven with simulated samples. It gives essentially no false positives or false negatives.
By shutting out the most valuable tests, the FDA is effectively disarming America in its life-and-death struggle with the virus. The FDA regulations do not consider the possibility that a test less sensitive than the “gold standard” might be preferred in public health, sacrificing unnecessary sensitivity to get necessary on-site speed. But speed is what we need.
False positives can always be eliminated by retesting, so that is not an issue. The FDA says, however, that it doesn’t want to “risk” tests that could produce false negatives. But by preventing mass testing, the FDA is effectively producing universal false negatives.
It any case, risk is best understood by those who actually face it. That means those of us who are trying to keep our workplaces safe, not those who are trying to show they followed standard procedures.
The coronavirus epidemic is a five-alarm fire. Effective action is long overdue. The FDA needs to get out of the way.”
https://app.getpocket.com/read/3064601649
Roger –
Yah. Makes no sense to me. Tests that take something like six days to get results are not nearly as useful even if they are more accurate. Yup, re-testing would be key. I can understand why initially, accuracy was the focus but we need to adapt. Also, pooled testing should be in use. Can’t understand why it isn’t.
And why aren’t we using emergency powers to increase PPE? Medical workers are still re-using one use equipment. Why aren’t we massively producing N95 masks instead of limiting people’s ability to buy them? Makes no sense.
Roger –
Yah. Makes no sense to me. Tests that take something like six days to get results are not nearly as useful even if they are more accurate. Yup, re-testing would be key. I can understand why initially, accuracy was the focus but we need to adapt. Also, pooled testing should be in use. Can’t understand why it isn’t.
Roger –
And why aren’t we using emergency powers to increase PPE? Medical workers are still re-using one use equipment. Why aren’t we massively producing N95 masks instead of limiting people’s ability to buy them? Makes no sense.
Joshua: “Why aren’t we massively producing N95 masks instead of limiting people’s ability to buy them? Makes no sense.”
There’s a lifehack for that:
Putting an N95 mask [or several] in an Instant Pot [for 1 hour with no water and with a large towel for insulation] decontaminates it: study
Last year’s hot kitchen appliance is trendy again — this time, for being a virus killer. Read in New York Post: https://apple.news/AvEzGav9KQp-xvtzRaROGQQ
Second wave Covid19 Cases and Fatalities
Nic How well does this support your argument?
The Ethical Skeptic plots Infection Rate, Fatality Rate, and All Cause Fatality rate, on Twitter. While the “infection rate hit 14%”, he shows the 2nd Covid19 wave cases appear to have peaked. 2nd wave Covid19 fatalities now appear to be peaking.
https://twitter.com/EthicalSkeptic/status/1287879425669783552/photo/1
David
EthicalSkeptic reaches broadly the same conclusions as I have, but more heuristically, without seeming to appreciate the importance of population inhomogeneity in social connectivity related susceptibility and infectivity, or modelling the path of the epidemic.
Nic Lewis
@Hold2LLC shows progressive peaks of cases in Arizona.
https://twitter.com/Hold2LLC/status/1289298833898274816/photo/1
Ethical Skeptic notes:
Real Developments finds Covid deaths follow Covid Like Illnesses in 2 weeks:
https://twitter.com/pdubdev/status/1288918211866501120/photo/1
But, assuming recovered individuals are immune, the pool of susceptible individuals shrinks over time and the current reproduction number falls. The proportion of the population that have been infected at the point where the current reproduction number falls to one is the ‘herd immunity threshold’ (HIT).
I wondered whether there was an operational definition or measurable attribute whose estimated value allowed you to say when HI had been achieved.
What confuses it even more is “overshoot,” where infections continue dispute prevalence hitting the putative HIT.
Might explain regions (or institutional settings) with a population infection rate at or above 60%.
I agree that overshoot, particularly in the absence of behavioural changes (whether voluntary or forced) that temporarily reduce transmission, is one reason for prevalence ending up high in some places.
However, I doubt that overshoot is the most important factor for explaining why prevalence is sometimes very high. In locations where prevalence reached something like 60%, assuming it genuinely did so, population heterogeneity in susceptibility and connectivity within that location was likely to have been relatively low, and the transmission rate high. That would cause the HIT in such locations to be much higher than for the country or region as a whole.
Herd immunity is generally said to be achieved when the current reproduction number (R[t]) falls below 1. This generally occurs marginally before the rate of new infections begins to decline.
“Herd immunity is generally said to be achieved when the current reproduction number (R[t]) falls below 1. “”
no.no. no
If a Population is Not practicing Any NPI and if they are mixing as they
normally would, and if R[t] falls below 1, then you have EVIDENCE that HI MAY be achieved.
For example. If I Locked up all citizens so that no one could leave their house R[t] would fall to zero, but herd immunity would NOT be reached.
I
Basically wuhan.
They must have quarantined all the K-Pop girls. Mosher suddenly has time to spend with us. But his comments are a very big improvement over the mindless chatter we get from PS #whatever and a few others, who drop by to snipe at Nic.
“no.no. no”
I disagree with your use of the term herd immunity, but I agree that the herd immunity threshold will vary depending on people’s behaviour, which depends inter alia on NPI.
So the fact that the HIT is low during lockdown, and has been reached then, does not mean that the epidemic will continue to decline once lockdown ends – as it must do, because continued lockdown causes great economic, health and social loss, as well as severely restricting people’s basic freedoms. Therefore, the HIT applying during lockdowns is of little relevance.
On the other hand, people may be happy to continue with moderate social distancing, with much lesser departure from normal life, for an extended period, if necessary, so HIT estimated in those circumstances is of much greater relevance.
That is one reason why I have focused on Sweden, where there have been only moderate restrictions, when estimating the HIT for COVID-19.
Under unchanging social distancing, the HIT is bound to be significantly overshot. Therefore, the final level of infection under a moderate, Sweden-like social distancing scenario may well exceed the HIT under a subsequent move to a no social distancing, normal life, situation.
From July 15 through July 31, there were 76 CV deaths in Sweden. There are currently 66,382 active cases, with only 40 in serious or critical condition. Total deaths to date, 5,743. NYC total deaths to date 23,002.
> because continued lockdown causes great economic, health and social loss, as well as severely restricting people’s basic freedoms.
Completely unintrospective subjectivity.
You have no way to prove that shelter in place orders “cause” economic, health, and social loss in comparison to the absence of shelter in place orders – particularly with the consideration of locality-specific factors.
It is exactly that kind of poor analysis that makes your policy advocacy suspect.
Likewise with your facile characterization about “restricting people’s basic freedoms.” The majority of people, in this country at least, support the issuance of shelter in place orders. As such it is a basic freedom for them to have their representative democracy act in accordance with their wishes.
The descriptor of” basic freedoms” is subjective. You’re entitled to your view. But it would be undemocratic for you and the minority of people who agree with you to dictate to a majority as what their “basic freedoms” comprise.
The cohort who argeee with you as to the civil liberties implications of shelter in place orders already enjoy power in policy-making that is disproportionate to their numbers. It is rather remarkable to see people who enjoy such disproportionate power put on display their self-victimization and entitlement mindsets that leads them to think they’re being victimized, let alone displaying their naked condescension that leads them to believe that they should be advocating in the best interest of people who disagree with them – presumably under the misconception that they are in a better position to determine what’s in the best interests of the majority who disagree with them.
niclewis: Herd immunity is generally said to be achieved when the current reproduction number (R[t]) falls below 1.
I am getting the impression that this is hard to estimate/operationalize before the new case rate falls dramatically from its peak. Consider the estimates of the time course of Re in Tkachenko et al.
cardiovascular consequences of COVID-19 assassed via MRI in recovered patients.
https://jamanetwork.com/journals/jamacardiology/fullarticle/2768916?guestAccessKey=abfeb502-c1b6-4f59-a511-0171dc776f67&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jamacardiology&utm_content=olf&utm_term=072720
That’s not good. Adds yet another wrinkle to the whole “just the flu, let everyone get sick” mentality.
ya 1/3 of patients have sequelae that dont seem to go away.
Steven Mosher on July 31, 2020 “ya 1/3 of patients have sequelae that dont seem to go away.”
Can I politely ask what you mean by this comment?
The problem us the word patient I guess.
It is clear that most people who catch covid do not get ill. Often stated that up to 99% of people recover without sequelae.
The moment you use the word patient you are talking about a small sick subset of all people who catch covid. Elderly people, sick people, diabetics etc.
such people always have complications after any serious illness that persist in at least a 1/3 of them.
It is not covid specific, your misinterpretation.
The problems of low blood pressure and pressure areas lead to renal failure strokes and gangrene. Covid throws in an extra serve of thrombosis but basically a third if all seriously ill ICU patients will have ongoing sequelae, especially older patients.
I am grateful you raise issues and do not consider them drive bye. In this case though the takeaway message is that 99% of covid infected people have no sequelae.
Ta.
angech: I am grateful you raise issues and do not consider them drive bye. In this case though the takeaway message is that 99% of covid infected people have no sequelae.
The article, and Mosher’s comment, were about the subset of those who get sick (patients”) and recover.
Our attention seems to wander between the large number of people who have slight or no symptoms, and the small number who suffer seriously and of whom some die. It’s like “How many grannies have to be put at risk to get an auto factory (and its supply chain) back to full production?” “Your granny?”
The JAMA article about cardiovascular consequences of COVID-19 had multiple elementary statistical errors and has now been corrected. The authors displayed such incompetence that I don’t think much weight should be placed on the corrected version.
In addition to Nic’s comments,
A) Its premature to ascertain whether any damage from Covid is permanent
B) It ignores centuries of medical knowledge regarding the body’s recuperative and healing powers.
Pingback: Why herd immunity to COVID-19 is reached much earlier than thought – update |
Nic, how do you think the “G” mutation will affect the curves? It supposedly increases the infectivity, but not the severity of the disease.
LLD, a mutation that increases infectivity but not severity can be expected to become very widespread, and would cause a pro rata increase in the basic reproduction number R0, assuming no change to the latent or infective periods. A higher R0, with unchanged variability in susceptibility, leads to a higher herd immunity threshold. My modelling suggests that, for a case with rather lower variability than Aguas et al find (CV=1.5 for connectivity combined with CV=0.8 for susceptibility), the HIT increases roughly proportional to R0, at least over the range 2.4 to 4.
LDD: If the viruses with the G mutation were 10% more easily transmitted than those without, and if you assume that there have been 30 cycles of infection followed by transmission since the G mutation evolved, then you would expect 1.1^30 or 17.5 times as many new viruses with the G mutation as new viruses without the G mutation – assuming that we started with equal numbers of both. The non-G viruses did have a head start, but there were relatively few cases at the time they diverged. In theory, if you could find a location where the pandemic began with roughly equal numbers of both infections and relatively few cases were brought in from the outside, it might be possible to do an accurate calculation.
A simple exponential growth model may be overly simplistic, but a small advantage in transmissibility almost certainly translates into a big advantage over 30 (or more) generations. Since the non-G virus strain is still common, I suspect this means that the G virus has a very small advantage (less than 10%) in transmissibility over the parent strain. The G strain could be more or less deadly than the parent strain, but researchers would have to carefully control for age and co-morbidities to be able to detect that difference.
One of the questions related to modeling heterogeneity.
–snip–
… new evidence from South Korea shows that the age of children is also a vital factor to consider, with a large study indicating that older children seem to spread coronavirus on par with adults, even if younger children do not.
–snip–
Looks like a pretty solid study.
https://www.sciencealert.com/older-children-transmit-covid-19-as-much-as-adults-do-new-evidence-suggests
Also related…and very interesting.
–snip–
Among 10,592 of these household contacts tested in the study, 11.8 percent of people ended up also having COVID-19, whereas just 1.9 percent of non-household contacts (48,481 individuals all up) had the virus.
–snip–
Thanks; I’ll take a look.
Jeff –
> Given that you believe the president is uniquely responsible for all things Covid19:
Given that I never remotely said anything like that, let alone think it, I’m not going to bother t reaond to anything beyond that conditional clause.
He’s uniquely responsible for some things. Partly responsible for others. And not at all responsible for other things.
And I’d say that would apply to positive as well as negative outcomes for the last two descriptors, although with the positive they are fewer and farther in between.
That is obviously always true for the impact of any president, for example on the economy, state of race relations, etc.
thanks joshua I was going to post that.
There are a large number of data points that Nic just plain ignores.
probably doesn’t read korean
Any way
here is another
https://www.nytimes.com/2020/07/09/nyregion/nyc-coronavirus-antibodies.html
Bottom line:
There are 3 areas of uncertainty
1 “natural” immunity. Investigations into T cells are forth coming.
Nic will probably discount them. Instances of seroprevalence
well in excess of Nic’s assumptions ( 70%+ in some)
2. “variations in mixing” Congregate settings show very large attack
attack rates even when NPI are used. 50% or more,
3. Efficacy of NPI. Very hard to even ascertain how well people follow policies
With those three unknowns you can play a lot of games.!!
and with deadly consequences!!
From the CDC:
“Nonpharmaceutical Interventions (NPIs) are actions, apart from getting vaccinated and taking medicine, that people and communities can take to help slow the spread of illnesses like pandemic influenza (flu). ”
Useful reminder, that word “slow.” It doesn’t mean eradicate or stop. The only thing that will stop a virus is herd immunity- hopefully assisted by a vaccine.
The United States is in month seven of a highly contagious virus. It hit several cities hard. The number of “cases” from January-May is ridiculously undercounted (anyone really believe the mortality rate in France was 15%? Anyone?) The “surge” today is thanks to a surge in testing- The worst day in Virginia hospitalization wise was April 12- 3,000 tests were done that day, 484 new cases identified, 126 new hospitalizations. The last 8 days in Virginia averaged – 18,272 tests per day, 1,077 new cases per day, 17 new hospitalizations per day.
The 126 hospitalizations per day happened 30 days after lockdown. The 17 per day is more than 30 days after “reopening.” Anyone who believes that herd immunity hasn’t contributed significantly to that needs to do their own science and explain why.
Who is it that’s fond of saying “do your own science?”
Steven
You are not thinking straight.
There is nothing in the Korean study that Joshua linked to that cuts against anything I have argued or modelled.
Prevalence in Queens, NYC, is most likely substantially lower than 68%. That figure came from a far from random sample: the tests were taken at an urgent care center. The article quotes Prof. Denis Nash, an epidemiology professor at the CUNY School of Public Health, as follows:
“For sure, the persons who are seeking antibody testing probably have a higher likelihood of being positive than the general population,” said Professor Nash. “If you went out in Corona and tested a representative sample, it wouldn’t be 68 percent.”
Moreover, one would expect individual neightbourhoods of a city to have less variability in susceptibility and social-connectivity related infectivity than the city as a whole, or even more so to that in the state containing the city. The smaller the sub-unit, the lower the expected variability within it. And in densely populated areas one would expect the reproduction number to be much higher than for the population as a whole, and hence the HIT to be higher. There may be demographic differences that increase the susceptibility of the Queens’ population to infection. Moreover, when an epidemic progesses unimpeded the final proportion of people infected will be well above the herd immunity threshold. So it is not terribly surprising that a relatively high percentage of the Queens population became infected.
Incidentally, I suspect that most of the people in NYC who had COVID-19 antibodies were infected prior to lockdown or before it became fully effective. In the UK, the chief medical officer has recently said that the epidemic was probably already past its peak (implying herd immunity had been achieved) prior to lockdown.
The NY Times article cites a more comprehensive survey on antibody rates conducted by New York State. It says “That survey suggested that roughly 21.6 percent of New York City residents had antibodies.” The study itself (https://doi.org/10.1101/2020.05.25.20113050) appears to show 20.2% cumulative incidence of COVID-19, or 22.7% when adjusted for the test sensitivity and for not all infected people generating detectable antibodies.
> Moreover, one would expect individual neightbourhoods of a city to have less variability in susceptibility and social-connectivity related infectivity than the city as a whole, or even more so to that in the state containing the city. The smaller the sub-unit, the lower the expected variability within it.
Actually, I remember hearing that some?/quite a bit?/many? of the people who came to that clinic didn’t live in that neighborhood. It’s prolly wrong to assume that the seroprevalence found at that clinic is just a function of the neighborhood in which it is located.
> The “surge” today is thanks to a surge in testing-
This is clearly not accurate – as evidenced from the rise in hospitalizations and deaths (after a lag) in parallel with spike in cases, and in the exact same locations as where the cases spiked. Deaths started rising again significantly from 3 weeks to 1 month after the cases started to surge and they have continued rising since.
Not to say that an increase in testing isn’t a contributing factor, or that the increase in identification of asymptomatic cases or cases among young people aren’t important considerations. The rise in cases outpaced the rise in hospitalizations and deaths. Of course, improved therapeutics should also be factored in.
It was bad enough that people go out in front of the uncertainty a month ago to confidently attribute the rise in cases to a rise in testing – but to still hold on to that claim despite the subsequent evidence that eliminates some of the uncertainty and disproves the claim, is just weird.
Why would anyone do that? Weird.
What’s criminal is that we actually know so little about what caused the increase in cases. In places like Korea or Hong Kong, when they have an outbreak they do great work in uncovering the dynamics.
Why don’t we know more? Because our testing stinks (such long turn around times to get results) and our contact tracing stinks (in part, because there’s such a long turn around time to get the results of the testing). .
And why do our testing and contact tracing stink? Well, the explanation is multifactorial, but one of the main factors is that we have a widespread cult phenomenon in this country (that is well-represented in these threads).
Joshua: “It was bad enough that people go out in front of the uncertainty a month ago to confidently attribute the rise in cases to a rise in testing – but to still hold on to that claim despite the subsequent evidence…”
According to the statistics from the EU, the mortality rate in the EU/EEA +UK is 10.7%.
According to today’s stats from the Washington Post, the mortality rate in the US is 3.4%
Given that you believe the president is uniquely responsible for all things Covid19: Which is it? Did Donald Trump provide testing that gives us three times more accurate picture of case counts? Or did Donald Trump do three times better at controlling the virus (slowing it’s spread and treating) than the EU and, therefore, saved tens of thousands of lives? Or are progressives so uniquely devoid of ideas that they can think of nothing else to do than inaccurately politicize a virus?
I think it’s a combination of all three.
EU stats: https://www.ecdc.europa.eu/en/cases-2019-ncov-eueea
US stats: https://www.washingtonpost.com/graphics/2020/world/mapping-spread-new-coronavirus/?itid=sf_coronavirus_subnav
Joshua: “Why don’t we know more? Because our testing stinks (such long turn around times to get results) and our contact tracing stinks (in part, because there’s such a long turn around time to get the results of the testing).”
I posted extracts from an article saying that the fault for the long turnaround time is the FDA’s. My comment is at https://judithcurry.com/2020/07/27/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought-update/#comment-922517
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Nic: It is clear that people vary widely in the seriousness of the medical conditions that arise from infection with SAR-CoV-2. This is one possible definition for “variation in susceptibility”. However, the course of a pandemic is not determined by the seriousness of the illness a virus causes in a range of patients; the course of a pandemic is determined by how easily the person in question TRANSMITS to another people. Really deadly viruses like Ebola spread slowly because they incapacitate a patient too quickly and scare those in contact with the patient. Really deadly viruses slowly evolve into less deadly strains because such strains are transmitted more efficiently. In the case of COVID, there isn’t much correlation between the level of viral RNA and the seriousness of the resulting illness, but infectivity most likely does depend of the level of viral RNA in the respiratory tract of infected patient – relatively independently from how ill they are. Totally asymptomatic patients do have lower levels of viral RNA than symptomatic patients, but a pre-symptomatic patients often has lower levels of viral RNA after symptoms appear. Coughing does help spread droplets and aerosols, but a study on influenza showed that infectious aerosols are generated by shear forces in the narrowest air passages and don’t require coughing. Chest images show “ground glass” regions typical of viral infection in some otherwise asymptomatic patients. For all of these reasons, I think it makes sense to focus on the concept of “variation in connectivity” (or transmissibility) rather than “variation in susceptibility.”
Even worse, there are reports that lower levels of antibodies are found in patients after mild or asymptomatic infections and the levels of these antibodies are already falling. A person who wasn’t very susceptible to COVID might not be protected from re-infection for long enough to count towards the development of herd immunity. (I’m not a big fan of this idea, but it has gotten significant publicity lately.)
Frank
‘It is clear that people vary widely in the seriousness of the medical conditions that arise from infection with SAR-CoV-2. This is one possible definition for “variation in susceptibility”.’
It’s not using “susceptibility” with its usual meaning, which is how easily a person can be infected, irrespective of how severe the symptoms of their infection. That is the meaning I use.
The fact that few antibodies are formed or the anitbody level falls quite soon doesn’t mean that a person isn’t, or doesn’t remain effectively immune to SARS-CoV-2. Such individuals normally form and retain memory Bcells and T-cells that should suffice to provide effective immunity or near-immunity after antibodies have dwindled.
‘I think it makes sense to focus on the concept of “variation in connectivity” (or transmissibility) rather than “variation in susceptibility.”
I think both are relevant, but in my modelling I provide for “variation in connectivity” to have a considerably stronger effect than “variation in susceptibility.”
“Memory B cells (MBCs) are a B cell sub-type that are formed within germinal centers following primary infection. Memory B cells can survive for and repeatedly generate an accelerated and robust antibody-mediated immune response in the case of re-infection (also known as a secondary immune response”
Antibodies and antibody responses can be very confusing when looking at immunity. The initial antibodies that develop, IGM, are replaced by longer lasting IgG and the levels can persist forever or appear to drop away to nothing or sometimes, like in HepB take a long time to develop.
This results in people misinterpreting the immunity of the person or the cause of their immunity. One often sees misleading comments with Flu vaccines saying the efficacy of the vaccine wears off after a few months. The reality is the efficacy is always there, It is just the antibody level that has dropped because there is no infection to respond to. If the virus does get caught the B cells aided by the T cells, kick into overdrive producing masses of the antibody needed.
in the seeming absence of the antibodies, which are always there, but dormant it is easy to think that other causes of resistance might be important when really it is the antibodies that kick in grabbing the virus and then allowing the T cells to help.
Nic You have certainly convinced me that the mathematical equations describing the dynamics of pandemics can be modified in such a way herd immunity is realized at an earlier stage. The relevant question now is whether the slowing that has been observed in this pandemic is due to substantial heterogeneity in susceptibility or changes in behavior and public health policy.
The 1918 influenza pandemic occurred in multiple waves and some evidence exists that each wave was brought to a halt by a combination of fear and public policy. “Social distancing” appears to be a term that was used a century ago. The same influenza strain apparently also contributed to seasonal influenza for many years after 1920. It is possible that pandemics don’t end because the population reaches herd immunity, but because fear reduces contacts between people. A search for “herd immunity” and “1918 pandemic” turned up surprisingly few papers and no one citing herd immunity as the reason that pandemic ended.
R_0 for the 1918 pandemic in some areas was 1.6-2.0, suggesting that fear and public policy could have brought that influenza pandemic to a near stop well short of herd immunity (several times) more easily than the same measures have slowed the current COVID pandemic. And fear in 1918 was a much more powerful force, because that strain of influenza killed many in the prime of life. No matter how well your mathematics fits an observed slowdown (say in Sweden), the same slow down probably can be explained by a model that includes fear and public policy as factors. However, it is difficult use heterogeneous susceptibility to explain: three waves of influenza in 1918, the Washington choir super-spreader event, the Marion prison, etc. I wouldn’t be surprised if peer reviewers were asking Gomes et al to discuss whether such natural experiments are inconsistent with the hypothesis in their paper.
I omitted some references that discussing the three waves of the 1918 pandemic and how some researchers think the pandemic was successfully but not permanently interrupted by fear and public health policy:
1) “The 1918 influenza pandemic in New York City: age‐specific timing, mortality, and transmission dynamics”.
Results: “Four pandemic waves occurred from February 1918 to April 1920… The distribution of age‐specific mortality during the last three waves was strongly correlated (r = 0·94 and 0·86). With each wave, the pandemic appeared to spread with a comparable early growth rate but then attenuate with varying rates.” … “We propose mechanisms to explain the timing and transmission dynamics of the four NYC pandemic waves.” https://onlinelibrary.wiley.com/doi/full/10.1111/irv.12217
If the most susceptible had been depleted by earlier waves, the early growth rate of subsequent waves should have been slower.
2) “Quantifying social distancing arising from pandemic influenza”.
Abstract: “Local epidemic curves during the 1918–1919 influenza pandemic were often characterized by multiple epidemic waves. Identifying the underlying cause(s) of such waves may help manage future pandemics. We investigate the hypothesis that these waves were caused by people avoiding potentially infectious contacts—a behaviour termed ‘social distancing’. We estimate the effective disease reproduction number and from it infer the maximum degree of social distancing that occurred during the course of the multiple-wave epidemic in Sydney, Australia. We estimate that, on average across the city, people reduced their infectious contact rate by as much as 38%, and that this was sufficient to explain the multiple waves of this epidemic. The basic reproduction number, R0, was estimated to be in the range of 1.6–2.0 with a preferred estimate of 1.8, in line with other recent estimates for the 1918–1919 influenza pandemic. The data are also consistent with a high proportion (more than 90%) of the population being initially susceptible to clinical infection, and the proportion of infections that were asymptomatic (if this occurs) being no higher than approximately 9%. The observed clinical attack rate of 36.6% was substantially lower than the 59% expected based on the estimated value of R0, implying that approximately 22% of the population were spared from clinical infection. This reduction in the clinical attack rate translates to an estimated 260 per 100 000 lives having been saved, and suggests that social distancing interventions could play a major role in mitigating the public health impact of future influenza pandemics.
“https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3226987/
3) “The effect of public health measures on the 1918 influenza pandemic in U.S. cities.”
Abstract: During the 1918 influenza pandemic, the U.S., unlike Europe, put considerable effort into public health interventions… There was also more geographic variation in the autumn wave of the pandemic in the U.S. compared with Europe, with some cities seeing only a single large peak in mortality and others seeing double-peaked epidemics. Here we examine whether differences in the public health measures adopted by different cities can explain the variation in epidemic patterns and overall mortality observed… In the subset of 23 cities for which we had partial data on the timing of interventions, an even stronger correlation was found between excess mortality and how early in the epidemic interventions were introduced. We then fitted an epidemic model to weekly mortality in 16 cities with nearly complete intervention-timing data and estimated the impact of interventions. The model reproduced the observed epidemic patterns well. In line with theoretical arguments, we found the time-limited interventions used reduced total mortality only mod-erately (perhaps 10–30%), and that the impact was often very limited because of interventions being introduced too late and lifted too early. San Francisco, St. Louis, Milwaukee, and Kansas City had the most effective interventions, reducing transmission rates by up to 30–50%. Our analysis also suggests that individuals reactively reduced their contact rates in response to high levels of mortality during the pandemic.
https://www.pnas.org/content/pnas/104/18/7588.full.pdf
Given enough intervention parameters or susceptibility parameters, one can fit “any” pandemic data.
“Given enough intervention parameters or susceptibility parameters, one can fit “any” pandemic data”.
I think you’re right about that. It seems the relevant factors include degrees of:
1- innate immunity that may protect many young people
2- T cell resistance that may protect some older folks
3- people who have actually been infected and have antibodies
4- distancing behavior whether by culture, fear, or mandate
#1 is probably high among the young
#2 is largely unknown
#3 is low in most populations that have been tested
#4 can vary greatly from country to country, state to state, even city to city
So with a major variable unknown and another varying greatly from place to place and not easily measured or quantified, any projection can be made. Some retrospectively will turn out to be right.
Above I wrote: “Given enough intervention parameters or susceptibility parameters, one can fit “any” pandemic data”.
That statement should be revised. It is hard to explain a multi-wave pandemic (caused by a effectively homogenous strain of virus) by relying only on variation in susceptibility. Explaining a multi-wave pandemic requires something that changes with time besides immunity – which only increases with time.
Unfortunately, we don’t have as definitive data about the 1918 pandemic as we would like (though the causative agent of the later waves was sequenced around 2005). The main source of data is “excess deaths”. Were all three waves caused by the same virus? (The first wave apparently was less deadly to middle age people.) Did getting infected in an earlier wave prevent re-infection in later waves? (Probably in the case of the second and third waves; possibly in all three.)
Surely variation in connectivity – which causes near perfectly correlated variability in both susceptibility and infectivity – is the prime explanation for super-spreader events.
I think individual prisons are much more homogeneous locations, particularly as regards connectivity, than a whole country or region, and they are high density, largely indoor settings. So one would expect the HIT to be high in them.
I agree that people’s behaviour changed in reponse to the epidemic because of the fear factor, together with legal restrictions, which reduced transmission and (temporarily) lowered the HIT. But behaviour has been returning towards normal, particularly among the young and in countries where the government has relaxed restrictions and didn’t pursue a “project fear” approach. Life sounds back fairly much to normal in Sweden now, but COVID-19 infections and deaths are continuing to decline.
Nic Lewis
Sweden’s average Covid19 fatality rate has dropped >97% from about 100 mid April to less than 3 down – with no lockdowns.
https://twitter.com/pwyowell/status/1289199855093420032/photo/1
without praising or condemning sweden, most all the countries that had massive infection rates and death rates early are currently having near zero infection rates and death rates ( at lease least relatively low./zero rates)
England,
france
spain
sweden
New york
The observation is that letting the virus run its course may be the best short term and long term solution.
Interesting. All countries…er, except NY.
US has had a high infection and death rate for an extended period – but instead of the US you singled out, NY
Spain infection rate has recently spiked. Too early to say if it will last
France’s 7-day average infection rate is still well below its highest, but it has doubled over the past weeks
Germany has been seeing a rising trend in recent weeks.
India has been on a long, exponential-like increase in cases and a long steady climb in deaths.
Brazil has seen a long steady increase in cases and deaths rose quickly then plateaued and stayed there.
And along with the dramatic reductions in death rates in those counties you mentioned, none of them have let the virus run its course, yet you point to their low death rates as evidence its smart to let the virus run its course.
But other than that, your comment was spot on.
“I think individual prisons are much more homogeneous locations, particularly as regards connectivity, than a whole country or region, and they are high density, largely indoor settings. So one would expect the HIT to be high in them.”
wrong. wrong wrong
serology in NY prisons showed a very low infection rate.
meanwhile India clocked in with 23% in Dehli.
it is NOT SIMPLY THE LOCATION.
it is a combination of factors for SSE
A) large numbers of people.
B) close closed setting. Like 15 people in a room with no
ventilation
c) EXTENDED face to face contact.
d) loud talking, chanting, singing, ect.
so 2 guys in a prison cell. not gunna happen, you get household attack rates.
mess hall?
depends
what is seating like?
what is ventilation like?
how long are they seated?
Joshua – you have an amazing ability to cherrypick, and miss the forest for the trees.
I singled out NY since that state (along with the NE corridor (NY, MA, CT & NJ) all had high early infection and deaths. Whereas, their rates are down dramatically.
Spain is having a relatively mild spike in infection and almost trivial insignificant minor spike in deaths less than 0.02% IFR using a 3 week delay from infection to death. granted it is approximate, but a reasonable estimate.
France has had a minor increase in infection rate since the middle of june – while the death rate remains almost non existent.
Same general trend with England/UK
Same general trend with Sweden
Josh – I am going to repeat my original statement – since you did not respond to primary point .
“without praising or condemning sweden, most all the countries that had massive infection rates and death rates early are currently having near zero infection rates and death rates ( at lease least relatively low./zero rates)”
Your mention of Brazil & India are not relevant to my comment – especially since they are too early in their infection cycle to have any merit or insight
“it is a combination of factors for SSE
A) large numbers of people.
B) close closed setting. Like 15 people in a room with no
ventilation
c) EXTENDED face to face contact.
d) loud talking, chanting, singing, ect.
so 2 guys in a prison cell. not gunna happen, you get household attack rates.”
I agree that not all prisons are the same, and that although the environment within individual prisons may be fairly homogeneous it may well vary greatly between different prisons. Although the HIT would be high in each prison relative to what it would have been if its population had been less homogeneous, it would still be low in absolute terms in a prison where the contact rate is low. That may have resulted from measures taken by individual prison authorities, of course – lock-up lockdowns.
Nic, thanks for this work which has been excellent. How do we get you onto SAGE?
We need people there who understand how models actually work.
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I posted this elsewhere, but it wouldn’t hurt to post it here as well:
> A New Understanding of Herd Immunity
The portion of the population that needs to get sick is not fixed. We can change it
https://t.co/FLwjQteJKm?amp=1
A lot of it focuses on Gomes and the implications of here work – among which is related to the impact of shelter-in-place orders, or social distancing without any such orders, on heterogeneity and therefore the modeling of herd immunity.
Lots o’ uncertainty to be had – which I’ll note that Gomes acknowledges even as she is confident in the application of her findings to the Covid epidemic. Too bad that lots o’ people treat the uncertainties selectively.
Joshua: It is worth noting that epidemiologists estimate R_0 from the early stage of a pandemic, before fear and policy have reduced the rate at which the virus spreads between people. They use that R_0 for calculating herd immunity (for example, in a vaccination program) because you don’t want uncontrolled spread when people’s behavior and policy return to “normal”.
Estimates of R_0 vary with locality. In the US and most of the world, the cumulative number of cases was doubling every two to three days in the early stages; 2.5 days in the case of the US in March. Big states began imposing lockdowns over several days beginning on 3/19 (and Americans saw lines outside NYC hospitals on TV), and the doubling time began increasing about week later. By 4/10, the rate of new cases was falling. In Sweden, however, the doubling time in March was closer to 5 days for some reason. For some reason – population density?, hygiene especially in public?, a tradition of staying home with a fever? – R_0 in Sweden was about half as big as in most other countries. This may partly explain why Swedish epidemiologists didn’t recommend a lockdown. Unlike the US, the doubling time for cumulative cases in Sweden didn’t abruptly change in early April, but it did gradually lengthen. Whether that gradual lengthening is due to approaching herd immunity or a gradual change in behavior isn’t clear. Models that incorporate fear as a factor in 1918 use a factor proportional to the current death rate, but the contacts that resulted in death occurred perhaps a week earlier in 1918 and more than two weeks with coronavirus.
Frank –
> his may partly explain why Swedish epidemiologists didn’t recommend a lockdown.
Yes.
One of the thing that discussants anxious to draw the conclusion that Sweden should be the model for everyone else sometimes miss is the basic and fundamental logic of what they’re arguing.
IOW, they don’t see that the reason why Sweden chose the path it chose is, at least in part, because of certain basic conditions. Would they have chosen the “herd immunity” path if they didn’t have the highest rate of single-person households in Europe? If they didn’t have such low rates of comorbidites in their population, such a good infrastructure for people to work from home, such good baseline health status, relatively low population density (averaged over the whole country), high general sense of social responsibility, high standard of living and mean income, good healthcare services available and affordable to everyone, low rate of multi-generational households, good social safety net to make sure that people wouldn’t suffer without government loans or ramped up unemployment, if they were located in closer proximity to Lombardy, if they had higher rates of travel to/from China???? Etc. Etc.
The same logic problem applies in the States – where people want to compare outcomes from different interventions in different sates merely by comparing outcomes, without controlling for the simple logic that differential outcomes are, to a large degree, a function of different starting conditions and that the implementation of different policy responses are likely to a large degree reflective of those different starting conditions.
Also (reposting from another thread), related to Gomes’ modeling – some quick responses from an infectious disease modeler. Not much in depth but still worth looking at:
https://threadreaderapp.com/thread/1286934165967892480.html
Work on evaluating non-pharmaceutical interventions in Brazil.
https://science.sciencemag.org/content/early/2020/07/22/science.abd2161.full
Info on excess mortality in Iquitos City, in Peru – where preliminary seroprevalence indicates an infection rate of 71%
https://twitter.com/Gabc91/status/1285641443172851712
So, if all of this is correct, then Iquitos may have reached herd immunity at a death rate of about 4.5 times what it is in the US.
Shows the uncertainty. Obviously, many relevant parameters (such as baseline health attributes) – including heterogeneity.
The population fatality rate in Bergamo was pretty close to that also.
57% in slums in Mumbai?
16% in non-slums (and climbing)?
Obviously, extrapolating from Sweden should be done along with carefully controlling for many complicated variables. But I can guess that won’t happen.
Anything else is effectively cherry-picking:
https://twitter.com/swapneilparikh/status/1288108188735164416?s=20
The ratio of case fatality rate to infection fatality rate in that tweet is really interesting.
So many unknowns.
That CFR/IFR ratio could be fodder for the HCQ crowd…
” I also projected, based on their declining trend, that total COVID-19 deaths would likely only be about 6,400. Subsequent developments support those conclusions. Swedish COVID-19 deaths have continued to decline, notwithstanding a return to more travel and less social distancing, and are now down to 10 to 15 a day. According to the latest Financial Times analysis,[12] excess mortality in Sweden over 2020 to date was 5,500, or 24%. ”
And now, 2 weeks after that analysis, deaths are up to 5700 – 100 more each week. If that rate continues (and a 14-day cumulative number of deaths running at 1.6 per 100,000 – the worst in Europe- suggests it could) it will be less than 2 months before your prediction is passed. Maybe better to change it to “only” at least 6400.
Reported deaths in Sweden two weeks ago were 157 below those currently reported (and 45 higher than the FT figure of excess mortality). That’s 79 more per week, not 100. Over the past four two-week periods, the increases in reported deaths have been declining quite strongly 471, 394, 212 and 157. On that evidence, I see no reason to change my projection.
Why do you think there will be 100 covid 19 deaths per week in Sweden in the next months when the trend over the past 8 weeks has been continuously downward, and the rate is already below 100? It is possible that by the end of the year Sweden will pass 6400 deaths, since there remain more rural regions were the virus has not spread as much, and these people certainly could catch the virus and add slowly to the total deaths. But that said, Nic appears to be right: the available evidence suggests a continuing decline in rate of deaths.
I don’t make predictions or state that “only” a certain number of people will likely die. Nic used a source which stated that there were 5500 deaths in Sweden up to the 13th of July. When I checked another source yesterday (which presumably used a figure up to the 27th of July, i.e. 2 weeks later) the total had grown to 5700, i.e. 200 more in 2 weeks, which means 100 more per week.
I don’t claim or predict anything but if that trend were to continue, especially as levels are increasing in many countries at the moment (and Sweden has the second highest 14-day cumulative rate per 10000 in Europe – after Romania, although it was the equal worst with Romania yesterday – who knows what it will be tomorrow: I don’t make predictions), Nic’s prediction of “only” 6400 deaths would be reached within 2 months.
He stands by his prediction. We’ll see…
“I don’t make predictions”. But you sure have no problem criticizing Nic’s… which suggests you believe his rational is mistaken. Very strange take.
Murph,
Well Sweden had 24 deaths reported from Jul 21-Jul 28. Only 39 new cases on last day reported. Of 65,495 currently infected cases there are only 43 in serious or critical condition. Based on your logic and prediction-denial prediction, Nic’s prediction looks quite plausible.
Nic Lewis is Mr. Jump to Conclusions on Covid and I suspect he has no idea what he is speculating about.
The pandemic is still in progress so there are no experts yet.
The number of people infected may be much larger than we suspect as many have no symptoms or mild symptoms.
The disease spreads quickly, mainly kills off the elderly and then death rates per day decline.
People in southern states move indoors more for AC in hot weather, then they get an infection spike too.
I guess the remaining “herd” is more immune to Covid death after the vulnerable elderly die off from it, often in nursing homes.
Nic Lewis speculates to get himelf published.
Not to advance medical science.
You suspect, but you can’t prove anything, because you are ignorant. Just offer up a bunch of vague generalities and a pathetic attempt at mind reading to divine a motive. You are a crank. We had enough cranks here, already.
Don Monfart
Your character attacks on me are not arguments. They do not make you appear to be intelligent. If that was your goal, then you are a great success.
Richard Greene
You are the pretentious little character assassin. Based only on your foolish and very ignorant suspicions, your argument is that Nic speculates to get published. That is stupid and everyone here but you knows it’s false.
Richard harsh words, not sure why you seem so upset?
You have a interesting way of defining expertise which would rule out all experts.
Nic puts a lot of time and energy into his thoughts and has a lot of expertise in the subject which he is us writing about. Which is applying maths and statistics to a model projecting possible herd immunity.
He is for all intents and purposes an expert in this field.
Re Vitamin D Deficiency & Covid-19
Nic Lewis There are growing statistics on Vitamin D deficiency correlating with Covid 19 fatalities. That varies with country and/or latitude. Adjusting for that may strengthen your analysis. e.g., See:
Daneshkhah A, Agrawal V, Eshein A, Subramanian H, Roy HK, Backman V. The possible role of Vitamin D in suppressing cytokine storm and associated mortality in COVID-19 patients. MedRxiv. 2020 Jan 1.
Biesalski HK. Vitamin D deficiency and co-morbidities in COVID-19 patients–A fatal relationship? NFS Journal. 2020 Jun 7.
Fernandes AB, de Lima CJ, Villaverde AG, Pereira PC, Carvalho HC, Zângaro RA. Photobiomodulation: Shining Light on COVID-19. Photobiomodulation, Photomedicine, and Laser Surgery. 2020 Jul 1;38(7):395-7.
Annweiler C, Cao Z, Sabatier JM. Point of view: Should COVID-19 patients be supplemented with vitamin D? Maturitas. 2020 Jun 8.
Pugach IZ, Pugach S. Strong Correlation Between Prevalence of Severe Vitamin D Deficiency and Population Mortality Rate from COVID-19 in Europe. medRxiv. 2020 Jan 1.
David,
Thanks. I will look at these articles. There certainly seems to be evidence that vitamin D deficiency is bad both for COVID-19 outcomes and more generally. As you say, this may be correlated across countries with COVID-19 mortality.
The evidence that a higher than currently recommended vitamin D level is beneficial seems less clear. I’m also not sure it is proven that taking vitamin D supplements helps that much, at least when the existing level exceeds the recommended level.
That last one is a textbook correlation doesn’t equal causation example, although they do appropriately caveat in the discussion (after saying vitamin D “explains” the correlation – but I know that’s fairly standard language).
That said, Annweiler et al. explicitly using Hill’s criteria for causation is good to see.
Nowhere near herd immunity hear in Antwerp, Belgium.
Covid19 cases are spiking sharply, lockdown returns with curfew added.
https://voer.edu.vn/file/55967
Here I will jump a shark. Those vulnerable to the virus are the hares. The virus is the lynx. The success of the virus follows the vulnerable. We are looking at the hare population attributes and inferring the virus population’s attributes.
So we try to break this natural relationship because after all, we are better than hares. Gods really. But us Gods want to go to work and socialize. And not be a college student who doesn’t get to go to college or a child who doesn’t get to go to school and socialize and eat.
This virus is a lot more successful than we are in the whole evolution game.
Swedish health officials said Tuesday that another 3,000 deaths from the novel coronavirus were likely in the country, known for its controversial softer approach to curbing the spread and much higher death toll than its neighbours.
The projection comes from one of three potential scenarios presented in a report from the country’s Public Health Agency on Tuesday.
In the worst scenario, where COVID-19 was expected to follow a traditional pandemic trajectory, over 5,800 more deaths related to the virus could follow.
That would be more than double the 5,646 deaths, out of 78,166 confirmed cases, so far recorded since the start of the pandemic.
https://medicalxpress.com/news/2020-07-covid-deaths-sweden-health-agency.html
I guess that would put Sweden on pace for ~900-1100 per million. If the US managed a similar pace we would probably have about 350-400,000 deaths.
Everybody good with that?
Jimmy, why would anybody be good with 400k deaths? You are a ghoul and what that rhymes with.
James –
Don’t worry.
Don explained there would only be @6,000 deaths.
Hi James. If we had France’s reported mortality rate (over 13% of reported cases ended in death), the death toll in the US (currently 3.4% mortality rate) would be 563,000 deaths so far- if we managed to be a good at governance as the French of course.
You’re fine with that, right?
Which is it- did the US outperform the EU in testing (giving a more accurate case count), or in controlling the virus (reducing mortality)?
In terms of public response to protect citizens- which would you prefer: a low mortality rate with a more accurate case count, or a high mortality rate with a less accurate case count? Does the fact that the latter would allow our “elite” to play political games in the newspapers and on blogs compensate for the additional deaths?
It’s for your own good because we can’t handle the truth.
https://i.redd.it/lio640f38ld51.png
Louie Gohmert — a Texas Republican who has been walking around the Capitol without a mask — has tested positive for the coronavirus.
…
Gohmert was filmed yesterday speaking face to face with AG Barr at a house hearing without a mask.
https://judithcurry.com/2020/07/27/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought-update/#comment-922167
Joshua,
The graph came from forum.arctic-sea-ice.net where there is a sub thread on COVID-19.
For the CDC vs HHS data controversy put this query into the Google or Microsoft news search engines:
Google: CDC HHS data change when:7d
Microsoft: CDC HHS data change (manually select ‘last 7 days’)
The big news on the forum these days is the the record breaking loss of Arctic ice.
As of 7/28/2020:
Sea ice area loss on this day 100 k, 47 k more than the 2010’s average loss of 53 k
– 2020 area is at position #1 in the satellite record.
– 2020 Area is 615 k less than the 2010’s average
– 2020 Area is 1,430 k less than the 2000’s average
– 2020 Area is 456 k less than 2016
– 2020 Area is 315 k less than 2019
– 2020 Area is 237 k less than 2012
Hi Jack,
That chart must look amazing for France.
i take it that your “argument” here is that the US is undercounting cases,which would, of course, mean the US did even better at saving lives than the formal statistics show. Our mortality rate is even lower than HHS reports.
Why would HHS want to downplay the country’s comparative excellence at limiting the damage caused by the virus?
Isn’t the purpose of public policy in a pandemic to limit deaths?
> Isn’t the purpose of public policy in a pandemic to limit deaths?
Well, that thinking explains a lot.
No, the purpose isn’t to limit deaths. It’s to limit spread – which logically will limit deaths but also hospitalizations, serous illnesses, sequelae from getting sick, pressures on front line workers, exhaustion of needed resources such as PPE, etc.
Cult mentality srikes again!
Jeff,
Which of those two factoids, verifiable record low arctic ice or trusting government ‘managed’ data is logically true? Isn’t that the point of controlling pandemic data, to inform and influence. There is some record breaking science and technology being done like never before in human history so I’m optimistic on on avoiding the worst outcomes.
As to that ice, well maybe the stadium wave theory hasn’t kicked in yet.
Jeff,
Was that the Didier protocol they followed in France?
All in all I would prefer something more like Korea. Shut down quickly and forcefully. Get everything under control, drive cases and deaths to almost zero. Open up with plenty of testing and contact tracing to put out any fires that spring up. We haven’t even mastered the testing part after 6 months of spread. Testing is useless if you can’t get results quickly and the mean time for results is days now.
“No, the purpose isn’t to limit deaths. It’s to limit spread”
That’s some industrial strength goal post movement there. The goal of public policy is to “reduce spread” of a virus? Really? Should we shut down the economy for the common cold- after all, who cares that it’s harmless, the only important thing is to reduce spread!
Of course the goal of public policy in infectious disease is to reduce harm. That was the entire point of lockdowns – at least as explained to us by Brix and Fauci – to flatten the curve.
And you’re still trying to avoid the corner you’ve painted yourself into. That mortality rate for reported cases means you either must admit that Europe has drastically underreported the number of cases (which kills your narrative that the US uniquely failed at preventing spread) or you must admit that Europe failed utterly at managing the harm caused by the virus (which means the US did a better job of protecting it’s citizens.)
Jack: “Isn’t that the point of controlling pandemic data, to inform and influence. ”
By underreporting cases, the EU is “controlling pandemic data” – it could be to misinform, it could be because there isn’t any real public policy need for an accurate case count of asymptomatic cases. Just as the WHO and CDC completely fail, annually, to accurately report every single case of the sniffles.
By inaccurately portraying the data, activists are “controlling pandemic data” to misinform and influence.
James: “All in all I would prefer something more like Korea.”
Well that didn’t happen in either the US or Europe because it was antithetical to either’s political social structure. So let’s analyze performance by comparing nations that couldn’t be Korea. Ooops, the anti-US narrative fails.
Jeebus –
> . The goal of public policy is to “reduce spread” of a virus?
Yes, it is to reduce (I should have said limit) the spread of a deadly virus that causes a lot of morbidiry and dangerous sequelae. The point being that the goal is more than to simply limit the deaths from the virus.
> Really?
If course.
> Should we shut down the economy for the common cold –
What?
> after all, who cares that it’s harmless, the only important thing is to reduce spread!
The spread of a deadly virus that causes a lot of serous illness. It’s not the common cold.
“Jeebus -”
It’s a highly contagious disease that kills people with identifiable comorbidities, absent a vaccine, the only “limit” you can impose on it is to slow it down and protect those it kills until herd immunity.
We did that and are continuing to do that.
The only way you can judge success is by comparing like areas. Based on readily available statistics we know Europe didn’t “prevent the spread” or protect it’s citizens better than the US. New York didn’t prevent the spread or protect its citizens better than Texas. Based on any competent read of their mortality rates either the EU is dramatically under-reporting the extent of the spread (obviously true) or they did a lousy job – compared to the US – of protecting the people it kills (quite possible).
Since there is no vaccine in Europe, either Nic’s right and the spread was so extensive herd immunity is approaching, or reopening Europe is gonna be just like reopening Arkansas. The Wall Street Journal today reports on reopening-related outbreaks in France, Spain, and Germany. Plus Japan, Australia, Hong Kong…
Like every other highly contagious disease herd immunity is the final destination unless an effective vaccine is developed and the track record is not good. Flattening the curve might be justified in some cases. How to get to herd immunity with the least overall damage should be the goal. Fantasies about testing, tracing, and isolation are just that fantasies for those with too much time on their hands. I assume that Josh fits this bill.
For those who don’t get out much, death is all around us and we accept millions of deaths per year in the US, many of which might be preventable (at least temporarily). Most sane people would have an acceptible level of excess deaths from any cause that would be justified to minimize total harm.
At any rate, Jeff,
Many states have effectively given up trying to limit the spread and certainly your boy ain’t going to do anything at the federal level before November and
nostradamusDon (6,000 dead in the US) Monfort guarantees a landslide.So it looks like you’re going to get your wish of unrestrained spread of the virus. Certainly preferable than having to wear a mask, right?
“The point being that the goal is more than to simply limit the deaths from the virus.”
# Deaths from virus
# Spread of virus
Rank the above assigning the highest goal to one of them.
You can rank one the highest goal but then cannot say however, or except for.
The idea is to have a goal and then to try to achieve the goal. Not to have two goals, not tell if you achieved your goal, can’t measure if you did, and have excuses because you don’t have one highest goal, or have it set up so you can always argue neither goal was achieved or you kind of achieved this other goal.
Swapping between the two goals for your own advantage is B.S.
“I guess that would put Sweden on pace for ~900-1100 per million. If the US managed a similar pace we would probably have about 350-400,000 deaths.”
“Everybody good with that?”
1 in 1000 with the bias to those over 65. Yes. Yes. Get back to work. Are you Okay with ruining the economy for the next few years?
Limiting the spread of the virus reduces deaths and illnesses. They aren’t separate goals.
Obviously, that needs to be weighed against economic impact.
Maximizing the economy is not a separate goal either.
In the non-binary world, those goals live in interaction with each other.
Which is why questions like this: “Are you Okay with ruining the economy for the next few years?”
Serve nothing other than a rhetorical function.
It suggests the simplistic mindset of a cult member. This is not an either/or choice, particularly since there is a huge economic impact from unchecked spread of death and disease at many levels.
“Limiting the spread of the virus reduces deaths and illnesses. They aren’t separate goals.”
That’s just not true. Until vaccine and herd immunity (which can be accomplished with a vaccine) the only limit is speed of the inevitable spread. This is highly contagious and half of the people it infects don’t know they have it.
Which means limiting the impact of the virus- keeping it away from the aged, sick and obese, improving treatment protocols (which includes not overwhelming hospitals).
Let’s chat briefly about using testing and contact tracing. Joe has Covid-19, but doesn’t know it because he feels fine. Why would he get a test? If someone talks him into getting a test for giggles, he won’t get the results for a couple days. When it comes back, the trace team knows he was positive for three days, but he may have been positive for weeks or even a month before that. And the team knows for every asymptomatic Joe who gets tested, there are 10 who don’t. Joe’s test result tells you the virus is in town. Unless you’re in the sticks somewhere, you already knew that. Joe’s test result says there are lots of infected people spreading the virus that you won’t identify by tracing. You already knew that because you follow the pandemic.
If you’re in charge of health, your best bet is to isolate the sick and elderly and prepare the hospital.
Which you also already knew, and were doing anyway, even before you saw Joe’s test results because that’s how you save lives and saving lives is the point of health care.
When you don’t have a highest goal, you’re saying nothing of value. You’re making it up as you go. There is nothing at the heart of you. Reducing deaths is a higher goal than the spread of the virus.
Attributes of a cult member: Having a goal. Stating that goal. Measuring results against that goal.
Average person: The virus spread to me. Are you dead? No. But it spread to you. We are doomed. I am fine.
RIP Herman ‘9-9-9’ Cain
RIP Bill Montgomery, co-founder of Turning Points USA
Both passed away after rejecting warnings to wear masks and practice social distancing but causation is not correlation and both had underlying comorbidity issues so COVID-19 was probably just a catalyst.
The herd is safe from them now.
Me? I’m doing just fine just waiting to cast my vote in 2024 since the 2020 election will be rigged per PDJT.
Hi Jack,
More than two people died in the EU this week. Shut it all down, right?
Anyone else notice that current downward slope of the cases after the uptick doesn’t correlate with the fact that restaurants opened and are still opened. But it sure does match up to attendance curves at the Democratic Party’s June/July mob festivals.
Hi Jeff!
I’ve switched teams. I’m now pro-pandemic since I figured out COVID-19 is carbon negative because every human that succumbs to the coronavirus eliminates hundreds of tons of CO2 and many other toxic effluents in the future.
Party on dude!
Economic goals are secondary to deaths from the virus goals. Two things are of equal value or not of equal value. It’s some math thing that’s important. This is binary. You can’t value one thing higher than the next thing. Par for the course. ask binary questions. Death is binary. If you want to not define a thing, and not know if you met your goal, you’re doing a good job. Here’s a participation trophy.
According to the latest statistics one American* human life is worth about $10 million.
https://www.marketplace.org/2019/03/20/how-value-life/
“But we do put a value on risks to life — we pay for safety features, we demand more for dangerous work. So the value of a statistical life is technically a measure of the value of risk, and it lets you compare the cost of a regulation in dollars to the benefit in probable lives saved.
That regulation back in the ’80s about labeling hazardous chemicals — it went ahead. The savings in lives and prevented injuries and lost days at work, all together, were worth the cost to businesses.
“Every major government regulation that involves mortality risks is assessed using the VSL,” said Viscusi.
So the value of statistical life is basically a way to value a life without actually valuing life itself.”
So $10,000,000 x 152,000~deaths = $1,520,000,000,000 or about 1 Jeff Bezos
*Many Americans are ZEVs.
Zero Economic Value Citizen: people for whom technology has rendered their skills or jobs without value. There are millions who have already dropped out of the workforce and are ‘ZEV’ citizens.
Rookie mistake. Old people are worth less. Less. Old people can be argued to cost us money. Like young people paying into social security to support them. You placed a value on lives. I adjusted it for age. So I am the monster. Safest path. Don’t put a monetary value on a life. But, plantiffs attorneys, who make our lives better.
Economic goals are related to deaths. That’s why openers talk of the deaths associated with the economic costs of shelter in place orders. It’s a legitimate point. It’s part of the balance.
> This is binary.
In a cultist’s mind, of course. In reality, not. If you focus on limiting illness, you’re necessarily focusing on limiting deaths, and that comes with economic costs and economic benefits. And non-cultists work to reconcile the interaction of the various goals.
> the Death is binary.
And that’s a totally different issue. Base two is binary also. Lots o” things are binary. But in the real world, the goals of limiting illness and limiting death are necessarily inter-related.
> If you want to not define a thing, and not know if you met your goal, you’re doing a good job. Here’s a participation trophy.
If you want to pretend that theres a binary choice, when the choice isn’t binary, and pretend that you’ve reached a binary (zero sum) victory, you can award yourself a participation trophy. Which is apparently what you’ve done. Congratulations on awarding yourself a pretend award for a pretend victory.
> “Limiting the spread of the virus reduces deaths and illnesses. They aren’t separate goals.”
>> That’s just not true. Until vaccine and herd immunity (which can be accomplished with a vaccine) the only limit is speed of the inevitable spread.
Ah. Another binary thinker. Imagine my shock.
A slower spread can lead to significantly less illness and a significantly lower loss of life. We’ve already likely seen a reduction in infection rate mortality becsuee of improved therapeutics and treatment. Thst means fewer deaths. Same for improvements in behaviors that can likely lead to reduction in viral load which likely can mean less severe illness and likely fewer deaths. Same thing for slower spread leading to a less over-taxed Healthcare system. And of course, if a vaccine is developed there could be a very significant differential difference in illness and death.
And once again, even if you ignore those aspects which we’ve already seen, and the potential benefits of future developments, a slower spread that slows down the rate of illness and deaths would have a differential impact because it would mean many people who have longer before they loose functioning abilities, and longer before the lose their lives. There are direct financial benefits represented from that one gainedz but it’s also of value to the people who get wick and die, and their families.
For example, it will take years for a country like Finland to reach the same per capita rates of illness and death fro Covid as Sweden has already seen, even if Sweden were to experience, zero illnesses and deaths from Covid starting right now. And they may never even get there! Especially if a vaccine is developed.
Stop with the binary thinking. It doesn’t serve you well.
> Let’s chat briefly about using testing and contact tracing. Joe has Covid-19, but doesn’t know it because he feels fine. Why would he get a test? If someone talks him into getting a test for giggles, he won’t get the results for a couple days.
Jebus.
Read something about testing and contact tracing and societal supported isolation in a country like Korea. It’s not like it can’t be done. That we’ve miserably failed at it doesn’t mean it can’t be done.
Again, step back from the binary thinking. Just becsuee we’ve failed at it doesn’t mean that it can’t be done or that it has no benefit.
So to sum things up. You can have two goals. That we can’t tell which is the most important. That we can never tell if we met either goal. Here’s your participation trophy.
If you would, state the goal. If you can’t state your goal, what is your argument? That you can’t state your goal? I can see we are making progress.
I think it is trouble in placing values on things. A GDP growth rate of 5% is no better than one of 2%. And GDP is not the proper metric anyway. Nothing has any value. Let’s go with that.
So the binary question is, can you place values on things? And your answer is no. But thing’s are not binary. So you have no answer. So do you or do you not have an answer? You can’t answer that one either.
Joshua: “Ah. Another binary thinker. Imagine my shock.”
You’re incapable of addressing my point- imagine my shock! I wrote that we flattened the curve and slowed the spread (everywhere Cuomo wasn’t governor), so the need is to focus on limiting the impacts of the spread, because spread will happen until a vaccine or herd immunity. We limited spread, time to reopen the economy and minimize the impacts of the virus.
Public policy focuses on saving lives and protecting (isolating) those who suffer the most from the virus. Meanwhile, cultists focus on the numbers of spread in communities that aren’t harmed and rely on inaccurate EU case counts to make political statements.
If you were clever, you’d make some sort of claim about infection rates among the younger working age population being a drag on the economy- sick people can’t work, even if it’s only temporary. This was the actual worry and cause of the hoarding in March, April, May. Remember all the scare stories about how outbreaks in packing plants would result in meat shortages?
But since the statistics don’t back that up- especially after the US successfully flattened the curve and limited both the spread and the impact better than the western world as a whole – you’re reduced to sophistry.
Hi Jack,
You didn’t switch teams, it was always population control. Y’all just didn’t get the bug you wanted.
Write this down: broke governments don’t waste money on windmills. Angela is feeling really good about having that Nordstream 2 pipeline coming online. I’d like to congratulate you on the successful policy implementation – in the nation best known for its “climate chancellor’ – to transition electricity production from zero emissions nuclear over to fossil fuels. Fossil fuels controlled by a heavily armed dictator in Moscow no less! Ain’t the 21st century grand? “Progressives” can succeed in regressive technology and geo-political retreats!
The 3,000 more death figure is for a scenario that sees “clusters of new cases around the country which would then quickly subside”.
Their third scenario, which you don’t mention, is one in which the spread of the virus follows current trends, and just over 200 additional deaths are expected.
Clusters of new cases are certainly a possibility, but wouldn’t one expect to have seen some of them,and the resulting deaths, already? If you plot rolling 7 day COVID-19 deaths, there are no non-trivial reversals from the downtrend after the mid-April peak, although the trend may be becoming shallower. And (per the FT analysis) by mid-July there were no virtually zero weekly excess deaths over the average.
> Clusters of new cases are certainly a possibility, but wouldn’t one expect to have seen some of them,and the resulting deaths, already?
You think the lack of such clusters is because of herd immunity? Despite that there are parts of the country that have seen few cases, not approaching anywhere near even 10%? Seems unlikely that herd immunity would explain a lack clusters on a country-wide scale.
Joshua- how does the virus get from an area where it was prevalent to an area where there were very few cases?
Since it doesn’t spontaneously appear, the method is travel between Stockholm (for example) and the hinterlands. If herd immunity is limiting the spread in Stockholm, it’s limiting the opportunity to infect travelers.
The other method, of course, is inter-country travel. In the US, the state of New York, which once sued other states for limiting New Yorkers’ inalienable right to visit at the height of the pandemic, now places limits on the inalienable rights of residents of other states to visit New York. The media says both NY policies were correct, of course.
Smarmy brainwashed left loon NYC AOC dismal Congressional district dwelling smarmy public school teachers think that capo di tuti Cuomo and his underboss Commie De Blasio have done a good job, way better than Orange Man Bad, of dealing with the virus. Facts, that somehow made their way into the NYslimes;
https://www.nytimes.com/2020/05/07/us/new-york-city-coronavirus-outbreak.html
Travel From New York City Seeded Wave of U.S. Outbreaks
The coronavirus outbreak in New York City became the primary source of infections around the United States, researchers have found.
Don. We saw NY and NJ license plates in late March and April in Virginia. New Yorkers fled the city in droves at the very height of the pandemic while lecturing us rubes that THEY were the ones doing they’re part and “sheltering in place”- the laughable phrase that Joshua likes to use.
That helped this spread.
But that said, New York’s status as patient zero probably has more to do with it being the center of business and tourism travel and an entry point for foreign visitors. If this country’s scientific, political and media elite ever sober up, there will be a real discussion about whether it ever was possible to “lock down” a city like New York to prevent spread much less ethical to force national bankruptcies of small businesses across the nation out of some misguided sense of solidarity.
The only public policy that really would have prevented spread was a shutdown of incoming foreign visitors, followed by strictly preventing NYC residents from leaving town, quarantining anyone who had traveled to the city, and then implementing as best you can anything that might slow the spread within NYC – maybe by making them wear the masks they told them not to wear during the worst of the spread.
And don’t tell me that locking people in the city violates their civil rights- I have family traveling up in NY now and, depending on where you’re from, the state of New York is issuing mandatory orders to report your movements within the state to NY officials, not leave your hotel room for two weeks, and threatening $10,000 fines for non-compliance. It turns out we’re not on the list of prohibited originations, but it was nerve racking since that list was ever shifting and varied depending on which official NY source you looked at. Right up to the day before they crossed the border it wasn’t clear if they needed to report to Comrade Covid. We told them to just tell the virus cops that they planned to loot fifth ave and they’d let them right in with no questions.
Given the horrific performance of NYC, you can bet that the exodus of infected people in the next pandemic will be three times as bad. The rest of the nation will be 10 times less willing to accept the New Yorkers ignoring the lock down orders.
But CNN hosts and NYC residents – like Fredo Cuomo – will boast of their adherence to “stay at home” orders. Just not, you know, at THAT home. The other one, the one that’s not in NYC.
Ain’t it weird that our smarmy little NYC-AOC public school teacher has got the hates on for Sweden, when it’s his own negligent and bumbling state and local regime that has seeded the U.S. with the deadly thing.
Sweden- deaths 5730, at the rate of 567/1m
NY- killing fields dead 32,725, at the rate of 1682/1m
NJ-subsidiary of NY regime dead 15,873, OMG! 1787 per million
Other nearby states- MASS and CONN competing very closely are tied, each with 1241 dead per million
I would gladly trade NY and surrounding areas with all the turnstile jumpers, rioters, cop haters, junkies, mindless drive-by varmints and smarmy PS school teachers, for Sweden.
Yes Jeff, The media have been doing a good job at their whitewashing of Cuomo and Murphy.
I am shocked shocked to discover that people are travelling from state to state in the United States of all places.
I think we should quarantine all of the hot spots – Florida, Texas, Georgia, Alabama – you know basically the South. Nothing in or out. That includes trains, planes, automobiles, trucks, and bicycles. We probably should closely monitor bird migrations too.
James: “I am shocked shocked to discover that people are travelling from state to state in the United States of all places.”
Define “lockdown.” One that says you can’t go to the corner bar is a restriction on movement and activity. But if that same order says you’re free to dash off to the beach in other states, it is a “lockdown” with with strange caveats that serve only to spread the disease far and wide.
Then there is the question of equity. New York’s governor objected to any restrictions by other states on travel by New Yorkers during the height of the pandemic, yet now imposes them on travelers from other states. Travelers from 36 states are essentially banned from visiting New York (unless they can stay in a hotel room for 14 days with no contact).
Which New York policy was wrong in your opinion- the one demanding freedom of interstate travel or the one restricting interstate travel?
And why would any competent media or “expert” class say (as they do now) “both were right, yay Democrat!”
https://coronavirus.health.ny.gov/covid-19-travel-advisory
Any lockdown restricts people’s movement.
Write that down.
If you’re going to limit people, do it effectively.
If you’re going to issue shelter-in-place orders, do it effectively, and do it early. The longer you wait the more you run into the possibility that the orders will have a diminishing benefit
Yo jimmy, the West Coast had the virus first and people from the West Coast travel. But it’s NY that Cuomo Seeded the whole country. Capo di tuti Cuomo and his very dim underboss Commie De Blasio encouraged folks in NY to party on. Don’t be scared, they said. We got this. Get out to the bars, restaurant, massage parlors, basketball courts and needle parks. Go to the Chinese New Year parade to show you ain’t scared and then do some traveling. But you left loon smarmy PS “teachers” give them a pass and blame Trump. Pathetic.
Density of population no excuse for Cuomo-De Blasio COVID carnage in NY. New Yorkers would have been better off in the slums of Mumbai. Mumbai population of 12.5 million with 6200 COVID deaths and possibly having now reached a semblance of herd immunity :
https://www.bloomberg.com/news/articles/2020-07-29/herd-immunity-seems-to-be-developing-in-mumbai-s-poorest-areas
“With social distancing more or less impossible, Mumbai’s slums are singularly well-suited for the coronavirus’s spread. Dharavi, the largest, packs a population as big as San Francisco’s into an area the size of New York’s Central Park, with as many as 80 people often sharing a public toilet, and families of eight regularly packed in a 100-square-foot room.”
Just think what a disaster Cuomo-De Blasio could have wreaked, if they were in charge of Mumbai.
https://www.bbc.com/news/world-asia-india-53576653
“More than half the residents of slums in three areas in India’s commercial capital, Mumbai, tested positive for antibodies to the coronavirus, a new survey has found.
Only 16% of people living outside slums in the same areas were found to be exposed to the infection.
The results are from random testing of some 7,000 people in three densely-packed areas in early July.
Mumbai has reported more than 110,000 cases and 6,187 deaths as of 28 July.”
Doesn’t our little TDS AOC acolyte thread bomber have anything to say about how poorly his Marxist-doofus NYC has handled the thing compared with Mumbai? Fuggetabout hating on Sweden for a while and look to your own mess. You voted for those left loon clowns.
Mumbai: 12.5 million people,
6200 deaths
“With social distancing more or less impossible, Mumbai’s slums are singularly well-suited for the coronavirus’s spread. Dharavi, the largest, packs a population as big as San Francisco’s into an area the size of New York’s Central Park, with as many as 80 people often sharing a public toilet, and families of eight regularly packed in a 100-square-foot room.”
NYC: 8 million people with gold paved streets and a surfeit of toilets,
23,000 dead
Shame on somebody.
For Mr. 132:
Maybe it’s the hydroxycholoroquine.
Don –
You’re really smelling yourself with this brilliant Mumbai to NY comparison aren’t you? I mean I know you’ve got some serious CDS, but you should slow your role or you’ll wind up with egg all over your face like happened to with your 2,500% off 6,000 deaths in US prediction, or when you cry like a wimp and say you’re not going to read any more if my comments 10 or 25 times (before you beg me to punish you by embarrassing you like the little bad boy deserves).
India as a country has much better results than the US. Around 1/3 the cases as the US and around 1/5 the deaths despite having 5 X the population. So by your logic your boy screwed up big time, but when anyone even suggests that you squeal like a stuck cult member.
Lots o’ confounding factors with cross-country comparisons, but since you’re so in love with the Indian government, please explain which policies of theirs is it that you think explains why India under Modi has done so much better than the US under Trump? Was it their strict lockdowns? Oh way, that would require you to think outside the cult member box, wouldn’t it? Can’t that, could you? Your fellow cult members might turn on you and accuse you if having TDS.
Of course Cuomo and Deblasio could have made better decisions. In hindsight we can always say that. But which of their policies were you saying in real time were a mistake, rather than relying on cowardly cheap shots based on hindsight? Go ahead, tell us which locors you criticized in real time? On the other hand, your boy did tons o’ things that people pointed out in real time were going to cost lives. We could start with his lies about testing. If he could have admitted the errors with testing months ago we could have started correcting the problems. But when cult leaders refuse to acknowledge errors and their cult followers fluff their dear leader instead of holding him accountable, he just continues to lie and shirk accountability.
At any rate – yes they all makes mistakes. Some of those mistakes are understandable but they’re mistakes nonetheless. Deblasio could have shut down sooner just as Trump could have shut down sooner. Cuomo should have made better decisions about the seniors in senior living facilities. But as much as I know you’re cheered by old people dying in New York nursing homes, the fact remains that the % of dead in New York nursing homes is below average compared to other states around the country. That doesn’t excuse his errors. Errors are errors. But consider stopping with the cowardly hindsight cheapshots because they only expose a rabid and partisan cult member – and we know that you’d never be one of those. Lol.
Anyway, Don, yah, Cuomo and Deblasio made errors that cost lives. Serious people can admit something like that. Only fools lie to themselves to pretend that their cult leaders don’t make errors – when those errors are obvious to see
Oh, and this whole AOC district public school teacher is just wacky. Do you really think you’re on to something there? ’cause if you do, let’s put some money on it. You’re totally wrong but maybe you’re foolish enough to continue to believe it long enough for me to get some money from you before you lose it investing in loser drugs.
BTW – stop mentioning Mumbai on this thread about 10% herd immunity that Nic is so sure of. That 60% infections in the Mumbai slums makes Nic’s confidence a bit problematic. Wouldn’t want that to happen, now would we?
BTW, Don –
I loved how you tried to handwave away your 2,500% off prediction about deaths in the US by saying it was because you’re “optimistic.”. That was beautiful.
It wasn’t because you were taking out your a$$ on a topic you know nothing about. Yah. That couldn’t be it.
It was because you were “optimistic.”
Too funny.
Don’t ever exchange, Don. We love you just the way you are.
Oh, and I certainly hope that “bye” wasn’t another lame promise to stop reading my comments. I can’t tell you how upset the very thought makes me!
“The coronavirus outbreak in New York City became the primary source of infections around the United States, researchers have found.”
Not Stockholm, not Stockton, not Mumbai, not Managua but left loon Marxist-doofus NYC. Who is going to pay for that? Trump?
They can’t eve think of names for schools. PS # whatever. No wonder their school system is a total failure. Who is going to pay for that? Trump?
They tried to push their salsa on us and we wouldn’t buy it:
Judith will probably delete most of this but somebody needs to deal with these smarmy thread hijackers.
I’ve been thinking about how people are making assumptions about the impact of Sweden’s policies choices, by backwards engineering from outcomes like deaths and change in rate of deaths and changes in rate of identified infections, etc.. That could be a facile way to look at it.
Cases per capita in Sweden are at 7,868 and cases per capita in Spain are at 7,008.
Sweden has conducted significantly fewer tests per capita, @80,000 per million as opposed to @140,000 per million in Spain
So Sweden has done considerably less testing per capita and identified somewhat more cases per capita. That would be consistent with a faster spread as a result of governmental policy.
But perhaps Sweden has done a more targeted testing – so maybe their positivity rate is higher. And so the ratio of tests conducted to cases identified may not tell the whole story.
I’m thinking that the differential impact of Sweden’s policy approach compared to Spain’s may not really be as different as one might expect with respect to speed at which the countries are approaching the putative HIT.
Perhaps I’m biased.
But if there really were a huge impact from government policy, I would expect the cases per capita to be more dramatically different.
Of course, it’s really precarious to compare across countries, with so many important variables that need to be accounted for to make any meaningful conclusions. That would be true for evaluating the effect of heterogeneity in each country, respectively, as well as the effects as measured by deaths per capita.
And perhaps the more “intrinsic” aspects of the comparative situations is more explanatory than government practices, per se.
Just sayin’.
Thinking about it, a much more more instructive comparison would be Sweden to its Nordic neighbors.
Hmmmm.
Norway, tests per capita = @79,000 = similar to sweden
Cases per capita = 1,687…less than 1/4 Sweden….)
Denmark @ 257,000 and 2,353
Finland @62,000 and 1,338
Maybe the numbers really do show that the trajectory of the pandemic is a direct function of the policies…. which is weird because from what I’ve seen the behavioral manifestations of the policy differences in the Nordic countries are not thst different (i.e., similar drops in mobility)
You are guessing final scores at half-time.
George –
Fair point. Although I would say beginning of first quarter.
“Although I would say beginning of first quarter.”
Why play your game?
I’ll go with the 5th inning, though the game may drag on as the Left continues hitting foul balls from wild, sloppy swings. The best they can do are dying quails, it appears.
While a few COVID walks were apparent in January, the Lefts game didn’t get frantically serious until around March, when they put their best spitball pitcher on the stinking NY mound. Let’s remember the foul racist cries towards the red team for keeping Chinese players in the dugout in January; and of course NY officials were advising fanboys to hit hot dog concessions with abandon until much later (broadcasters were widely announcing there was nothing to worry about early in the game).
Maybe we’re at the bottom of the 6th? It’s hard to maintain attention watching a sloppy game. The ump is checking the scoreboard, it appears there’s some funny business going on with the count.
The home team medic, Fauci, has a fairly high degree of confidence the game will end sooner rather than later, “cautiously optimistic”, in his own words; that we’ll have a good shot for finishing the game by years end. This seems reasonable if we can keep him off the mound.
A promising shot in the arm performer just moved into phase 3, aka Triple A. The red team has a good farm system; 10 possible winners in the pipeline, 2 more moving up to Triple A soon. The blue team would prefer to hold their farm system back till next year in hopes they can get a better draft pic; they’re satisfied with paying off umps and stinking up the place till then.
Jack –
What’s your source for that graph? Also, aren’t the hospital reports and other still available to Johns Hopkins and other consolidators of data? By what mechanism could the HHS actually alter the data? Also, well have to see if there’s a discrepancy in data on hospitalizations and deaths which might be harder for HHS to control.
Correlation doesn’t equal causation.
positivity rates for Latinos in the JHU catchment area:
https://jamanetwork.com/journals/jama/fullarticle/2767632?guestAccessKey=021db7f7-cf8b-4cd3-984e-03a426f75c50&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jama&utm_content=etoc&utm_term=072820
sample: The daily positivity rate was higher for Latino patients than patients in the other racial/ethnic groups (P < .001 for each pairwise comparison; Figure, A). Moving average trends in positivity rate peaked later for Latino patients at 53.4% (95% CI, 49.6%-57.3%) on May 10, 2020, compared with white patients (16.1% [95% CI, 14.1%-18.3%]) on April 16, 2020, and black patients (29.6% [95% CI, 26.9%-32.6%]) on April 19, 2020. As testing volume increased over time for all racial/ethnic groups (Figure, B, C, D, and E), positivity rates declined (Figure, A).
school closures and COVID-19:
https://jamanetwork.com/journals/jama/fullarticle/2769034?guestAccessKey=bcaed1ea-2f56-41a8-a4e7-b9e526931aa6&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jama&utm_content=olf&utm_term=072920
snippet: In this US population–based time series analysis conducted between March 9, 2020, and May 7, 2020, school closure was associated with a significant decline in both incidence of COVID-19 (adjusted relative change per week, −62%) and mortality (adjusted relative change per week, −58%). In a model derived from this analysis, it was estimated that closing schools when the cumulative incidence of COVID-19 was in the lowest quartile compared with the highest quartile was associated with 128.7 fewer cases per 100 000 population over 26 days and with 1.5 fewer deaths per 100 000 population over 16 days.
Closure is confounded with other state differences. Not as well done as the German study of lockdown orders, imo.
https://www.bloomberg.com/amp/news/articles/2020-07-28/sweden-unveils-promising-covid-19-data-as-new-cases-plunge?__twitter_impression=true
The countries most similar to Sweden – arguably Norway, Finland, and Denmark. I would be interested in reading someone knowledgeable about Scandanavia describe how alimentary are and whether other countries might be more like Sweden.
At any rate, looks like Denmark has a slight trend of increasing cases which could turn into a spoke but we’ll have to see. It may not.
Outside of that, the three other countries have still lower rates of infection than Sweden, and even with Sweden currently at a 7 day average down to 2 deaths its certainly no better than in those other countries.
Has Sweden experienced a less severe economic impact than those other countries. Doesn’t seem clear as of yet – although maybe to some degee.
Will it benefit differentially economically going forward compared to those other countries? I guess we’ll have to wait and see. Anecdotal reports seem to suggest thst people are social distancing at this pint to similar extents among those countries (if anyone has information on that, please provide a link).
Will it prove that Sweden’s massive sacrifice in deaths and illness are worth it in the end? That’s largely a subjective determination, but even then it’s too early to say, and even thefe the long term answer to that question will be a function of the development of therapeutics and a vaccine. Too early to say.
Beginning of first quarter.
Actually, “massive” is completely subjective as well.
But the fact remains that even if all infections and deaths from Covid stopped today, it would take those other countries years at their current rates to reach Sweden in absolute numbers of illness and deaths. Of course, rates in those other countries could increase and it could happen sooner. And of course, if a vaccine is developed, it would probably never happen.
Ultimately up to the people of Sweden to decide.
Extrapolating to other more dissimilar countries is obviously problematic (even though many want to ignore those problems), but I think it’s fair to say that the sacrifice for other countries if they had followed a similar trajectory – which keep in mind would be an unrealistically best case scenario because if Sweden’s structural advantages – would have been “massive” even if people want to judge it as worthwhile.
“Actually, “massive” is completely subjective as well.”
Yes. In that connection, I suggest that it is much more appropriate to measure the cost of COVID-19 deaths In terms of loss of quality-adjusted life years (QALY), a standard measure used to appraise the benefits of public health interventions, than in terms of crude total deaths. On that basis, the burden of COVID-19 deaths in Sweden appears to be almost identical to that of (largely respiratory disease caused) excess mortality in England (I can’t find suitable data for Sweden) during the 2017-18 flu season, measuring both as rates per million QALY expected for the whole population. That is because the average age of people dying from COVID-19 in Sweden is so high.
Nic –
> In that connection, I suggest that it is much more appropriate to measure the cost of COVID-19 deaths In terms of loss of quality-adjusted life years (QALY), a standard measure used to appraise the benefits of public health interventions, than in terms of crude total deaths.
That is hardly an objective measure. All kinds of subjective values embedded if you take a generic measurement of averaged years of expected life left to attach a value to one death versus another. Not to mention that there are all kinds of complicated compounds that would necessarily need to be taken into account – such as baseline health status, health behaviors, # of comorbities, predicted like race/ethnicity and SES. Not to say that the evaluation is irrelevant or shouldn’t be examined, but neither should the sticky social and values implications of those factors be ignored. For example, is a 70 year-old black man who supports two generations of children and grandchildren, and who has a comordibity, worth less than a 70 year old white woman who is healthy as a horse but suffers from schizophrenia and is institutionalized – even though her life expectancy might be much longer? Or flip the script, and figure out if a 70 year old man who runs marathons and eats a very healthy diet and has no comorbidities and lives in a life care community and lives in Sweden is worth less or more than a 40 year old man who has many comorbities and who never exercises and eats a poor diet and lives alone in Harlem and is not likely to get covid. You need very granular data to make those assessments meaningful. Data that we don’t have. Yes, you can do averaging, but there are a lot of moral Implications that you just can’t wave away. Answer them as you will. Different people will being different values to the discussion. But don’t just ignore them.
Here’s a discussion where statistically literate people (excluding my comments) weigh-in:
https://statmodeling.stat.columbia.edu/2020/05/13/years-of-life-lost-due-to-coronavirus/
And again – straight country to country comparisons could be very misleading if you don’t control for important country-specific variables – not to mention that you should be considering % of change in mortality rate in the one country compared to the other, and not a simple comparison of absolute numbers adjusted for the population.
It is blatantly obvious that what Nic said is correct:
“Yes. In that connection, I suggest that it is much more appropriate to measure the cost of COVID-19 deaths In terms of loss of quality-adjusted life years (QALY), a standard measure used to appraise the benefits of public health interventions, than in terms of crude total deaths.”
Arguing against this with elaborate jabbering prominently featuring the race card is just foolishness and futile.
QALY more appropriate measure than crude total deaths. Period. End of story. No need for all that useless self-agrandizing jabbering. Oh, look at what I said where statistically literate people gather. Putz.
Don –
> QALY more appropriate measure than crude total deaths
Thanks for reinforcing my comment I just wrote about sense of entitlement.
So nice of you to determine what is and isn’t the more “appropriate measure.” If only you could get the riffraff to fall in line eh? Those ignorant rubes insist on thinking that total deaths is the “appropriate measure” and keep using it! And imagine, they haven’t even asked you to decide for them as they should!
One would think that with your prognostication skills you put in display with your prediction of 6,000 deaths in the US from Covid, they would have learned to fall in line.
(and again, I love that you explained your 2,500% error as being a result of “optimism” rather than just you pulling something out your a$$ on a topic you know nothing about).
Oh well, such is the hardship of being the superior. I feel for you.
Don –
Here you go. Maybe you can take a few minutes out from hating and writing “left loon” long enough to read an article about Dharavi in Mumbai – in the WAPO, .. Shriek!! (I promise you won’t get the cooties if you read it).
https://www.washingtonpost.com/world/asia_pacific/how-a-packed-slum-in-mumbai-beat-back-the-coronavirus-as-indias-cases-continue-to-soar/2020/07/30/da859532-d039-11ea-826b-cc394d824e35_story.html?
And since you were praising the outcomes there, and wishing we had done as well here, maybe you can join me and agree that its a tragedy that our governments at federal and state levels didn’t take as aggressive an approach as they took in Dharavi.
Fortunately, it’s not too late for governors and you boy in the White House to learn from others – although in the case of your boy I put the chance of that happening somewhere between 0.001% and 0.002%.
Of course, I never thought that anyone could be as far off as 2,500% in predicting American deaths from Covid either – and you proved me wrong there!
Joshua, As usual, your article contains little beyond anecdotes. I thought I read recently that in some areas of Mumbai up to 2/3 had already been infected. It that’s true, the cause of declining cases could be herd immunity. India has a much younger population than most Western countries, so IFR’s would be a lot lower too. In any case, “cases” is a virtually meaningless measure.
pathetic
Since our resident left loon joker wants to talk about left loons, this is one he voted for. AOC’s Congressional district in NYC is definitely in the running for worst per capita corona virus death rate in the universe. But she is busy curing white supremacy:
https://twitter.com/johnrobertgage/status/1289216440088662016
So, the Democrat left loons won’t even give a Saint a break. Saint Damian was white, so he’s a white supremacist. Never mind that he went among native Hawaiian lepers turned out by their own people and cared for them at the inevitable cost of his own life from the terrible illness.
Nic Lewis, thank you for the essay.
About this assertion: herd immunity to COVID-19 is reached much earlier than thought
Can you support such a claim for any other country than Sweden? How would you be able to tell, for example, when herd immunity “is reached” in New York or Texas?
Has anybody taken one of these models and fit it to the data of a number of countries through June (separately for each country) and used the fitted models to (a) project the rest of the year; (b) test between-country differences in parameter fits (distinct from “explaining” any differences); or (c) tested whether parameter(s) changed on the date(s) of any lockdown(s) (i.e. a changepoint analysis)?
Dutch reportedly abandon masks:
https://www.reuters.com/article/us-health-coronavirus-netherlands/dutch-government-will-not-advise-public-to-wear-masks-minister-idUSKCN24U2UJ
except public transportation and airports
Herman Cain passed away today from COVID-19.
Cain should be honored alongside John Lewis as a 20th-21st century role model; these individuals distinguished the essence of what hard work, determination and perseverance could accomplish, irrespective of ones race, or creed. Both advanced from being disadvantaged within a racially charged society. John Lewis and others advanced civil rights; Cain demonstrated the fundamental power of the individual to advance through poverty to become a leader through perseverance. Both these figures capture a unique, but fundamental achievement that embraced inherent American founding principles granted through the Constitution and Bill of Rights.
More vaccine news:
https://www.nature.com/articles/s41586-020-2607-z
Above dpy6629 | July 29, 2020 at 8:15 pm | repeated a common, but grossly wrong statement: “Like every other highly contagious disease herd immunity is the final destination unless an effective vaccine is developed and the track record is not good. Flattening the curve might be justified in some cases. How to get to herd immunity with the least overall damage should be the goal. Fantasies about testing, tracing, and isolation are just that fantasies for those with too much time on their hands.”
Nonsense! Taiwan, South Korea, New Zealand, Australia, China and now Germany are currently PROOF BY COUNTER-EXAMPLE that herd immunity isn’t required to be the final destination of a highly contagious disease in the absence of a vaccine. Clearly testing, tracing and isolation can be effective.
The 1918 pandemic occurred in several waves often six months apart. That pandemic was stopped by fear and public health policy several times well short of herd immunity. By 1920, an estimated 33% of Americans had contracted the disease, but that is well short of traditional estimates of herd immunity. And the same strain of flu was present in seasonal influenza for decades afterwards – proving that herd immunity hadn’t been reached even in 1920. As a population approaches herd immunity, the exponential growth rate isn’t as explosive because a significant number of the contacts an infected person has are with those who are already immune. Those with the greatest number of contacts were more likely to be immune. Being partway to herd immunity means outbreaks spread more slowly and were easier to contain by fear and public policy.
Didn’t polio pandemics (with an estimate R_0 of 5-7 according to Wikipedia) end well short of herd immunity? FEAR is a great motivator to change behavior.
I’d caution against using Australia, as an example for your point, just now. The virus is well out and about in Melbourne and Victoria, with leaks into Sydney that may also be getting away (this makes up about half the population), and now cases in Queensland (starting with a couple of very dodgy characters, perhaps criminals, who lied to the authorities about having recently been in Melbourne). It’s a costly and ultimately grotesque game of whack-a-mole. At least in part, this second wave follows a security guard getting between the sheets with someone who was supposedly in mandatory supervised hotel quarantine (after entering the country).
The question to my mind is just how bad is this virus? Is it something we need to eradicate (like smallpox), or learn to live with. Given the difficulty of the former, I’m surprised to find it becoming heretical to muse on the latter.
Well, I’m assuming that polio is a special case in that those infected were mostly incapacitated. I don’t think however that there were any special public health measures implemented against polio, which was never very commonb. That leads me to believe the R can’t have been as high as you say or else most people had natural immunity.
In any case, testing, tracing and isolation in a free society are very difficult to maintain. And discipline and will always erode over time. So, its a solution that seems attractive to some with a certain perfectionistic or even authoritarian viewpoint, but it has never worked very well in the USA for other diseases.
Given the highly skewed profile of those who have died, and the smaller than initially thought IFR (which always decreases as an epidemic progresses), I would tend to believe that taking into account preexisting immunity we may be close to herd immunity in many places already. Life is dangerous and short of Howard Hughes levels of obsession and compulsion, I don’t consider it possible really to “stop this virus” at least in the US.
A question for you Frank. What level of excess mortality are you willing to accept from covid19 to avoid massive economic damage and large resultant future mortality?
“to avoid massive economic damage and large resultant future mortality?”
Which is similarly a myth. You cannot fight a myth with a myth. People losing money isn’t an economy. An economy is one that delivers needed goods and services to people, and the current economy is doing just that. What we are discovering is how much of the economy is actually needless fluff.
The “economic damage” doesn’t happen if you operate the economy properly – essentially ensure everybody short of a job has a job at a living wage paid Federally where the job is currently to keep out of the way.
That will auto-stabilise the system for as long as we want it to.
The issue is about individual freedom, not counting dollars. There are as many dollars as required to operate whatever production system we want to operate.
“People losing money isn’t an economy”
I meant people losing money isn’t economic damage.
NielW, Your comment is deeply inhumane. The excess mortality resulting from chronic unemployment is very well documented. Wealth is associated with longer life expectancy and more creative energy. This has been true throughout human history.
The 30 million who are currently unemployed in the US thanks to our mass panic attack over covid19 are important too. Their lives matter.
Your socialist nostrums have been a disaster where ever they have been tried. Free enterprise produces vastly more happiness and wealth.
Finally, your attitude is deeply dictatorial. People should decide for themselves what is “necessary” and what is “fluff.” That you, an anonymous leftist on the internet thinks he knows this with certainty is a sign of a personality problem. The other alternative is that you are an unemployed Bernie Bro sitting in Mommy’s basement with nothing else to do.
Bernie bro (probably PS #whatever teacher) says:
“The “economic damage” doesn’t happen if you operate the economy properly – essentially ensure everybody short of a job has a job at a living wage paid Federally where the job is currently to keep out of the way.
That will auto-stabilise the system for as long as we want it to.”
Why can’t we do what all the other countries are doing? Government operates the economy and auto-stabilizes stuff for as long as we want stuff to be stabilized. Properly. Modern Monetary Theory. AOC Utopian Econ 101: for Dummies.
If these loons succeed in getting power, we are sunk.
dpy6629: I won’t be allowed my choice of “tolerable excess mortality”. No democratic or authoritarian leader of a nation or locality with a reasonably advanced health care system is going to fail to take action to prevent citizens from dying waiting in line to get into a hospital or lying in hallways waiting for a bed! Given the absolute inevitability (IMO) of government action, I want government action that will bring the pandemic to a halt – not have it drag on indefinitely. Simply “flattening the peak” is a recipe for a multi-year depression and slow recovery. Many people won’t leave home unless they feel safe! The Swedes didn’t force businesses to close, but they suffered economic damages similar to their neighbors that did. And for some reason (population density? hygiene, less crowding in public places?), the cumulative number of cases was doubling in Sweden every five days in March, instead of the normal 2.5 days seen in most other countries, explaining why Swedish epidemiologists weren’t under immediate pressure to stop the exponential phase of their pandemic. Nevertheless, they have publicly acknowledged making the wrong call and apologized. The Swedes look at their neighbors and wish they had reduced their case load dramatically and were now returning to normal!
The difference between stabilizing (each infected person infecting an average of 1.0 new person) and winning (each infected person infecting an average of 0.8 or less new people) is darn small! With an incubation period between successive infections of about a week, in 10 weeks the case load can be reduced to 0.8^10 = 11% = 10-fold safer. 0.7^10 = 3%. The Chinese reached 0.3 and the Wuhan pandemic was totally stamped out by April 1. With an order of magnitude or more fewer patients, testing, contact tracing, and quarantine are more practical. (Offer anyone who has been exposed quarantine with free room in empty college dorms and hotel rooms with delivered meals. With adequate testing, quarantine can be shortened to one week followed by a test.)
Then you begin returning people to work, remembering that more contacts between people MUST be accompanied by safer contacts between people: Mandatory face masks, forehead temperature scans on entering schools, workplaces and public buildings, PCR assay data in less than 8 hours (instead of more than 2 days), hospital grade air filters in all public facilities – anything AND everything that MIGHT help, so that as many people can return to work as possible and still keep the new infection rate falling. 10 more weeks at 0.8 – 1% as many new cases a day = 100-fold safer.
Eventually, your pandemic will be reduced to localized outbreaks that can be stamped out with severe LOCAL measures and local universal testing.
In the hardest hit areas of our country, there are up to 100 new cases/day/100,000 people. If a person is infectious for an average of 10 days, 1% of the population is known to be infectious at any time, several times that many actually are infectious, and the case load is intolerably close to overrunning hospitals. Elsewhere, about 0.1% of the population is known to be infectious, a non-trivial cumulative risk for people who have potentially infectious contacts with a dozen people a day. So far, we have had about 4.5 million confirmed infections, 1.5% of the population. No matter what factor you favor for compensating for silent infections and calculating herd immunity, our pandemic and linked economic woes ARE GOING TO CONTINUE FOR MANY MONTHS TO COME, including re-opening schools and colleges this fall. As I noted elsewhere, the 1918-20 Spanish flu arrived in three waves, so the near halts in that pandemic were NOT caused by approaching herd immunity. If I’m correct about herd immunity, a “flattening the peak” strategy will mean several YEARS of the current mess.
I read, but lost track of, one paper that tried to identify the optimum (economic) strategy for dealing with an influenza pandemic. The authors concluded that the decision whether or not to intervene depended on the value assigned to jobs and to lives. However, the best strategy if intervention was chosen was the one that ended the pandemic as quickly as possible. Merely flattening the peak was expected to produce the worst economic outcome.
Thus I get extremely frustrated when usually-intelligent commenters fail to recognize that other countries are winning the fight against this pandemic, proving that we can too. Since intervention is a political necessity when a threat of overrunning hospitals exists, our only good choice is winning. The philosophical issues you pose above should yield in the face of reality.
Frank, that’s a pretty long winded response. I just don’t believe that the strategies you advocate can work in the real world as they have not worked with past epidemics unless the contagiousness was lower. One can look at California where they have had a very strict lockdown that essentially continues to this day. Yet cases are growing. Now its true that California has a large population of very poor people who don’t speak English and may not be aware of Newsom’s orders. Perhaps compliance in this population is low. Or perhaps young people who are already ready to tear down the system don’t care. Perhaps German’s are more inclined to “comply” with their elites than Americans. Most experts who I have read seem to believe that more waves are likely in places like Germany. The fundamental problem is human nature.
Whatever the case, those states with the most stringent measures also seem to have had the most deaths per capita. And hospitals were never even close to being overwhelmed except possible in NYC. Speaking of this is really scare mongering. Just as the “ventilator crisis” was largely not justified.
The only case in which your ideal world strategy is worthwhile is if a vaccine that is effective shows up soon. The track record is not very good. But the economic damage is profound. I fully expect the financial system to approach collapse when mass defaults and bankruptcies start happening. The only alternative may be a massive devaluation of currencies which in the past have been ruinous. A whole class of people who have accumulated some moderate wealth will be ruined, many of them retirees.
The insanity of this can be seen by asking yourself if you want to lower speed limits to 10 MPH to save 45,000 lives a year. No sane person advocates this approach because public policy is always a balance between lives saved and convenience and freedom. If everyone had followed public health advice, we could have wiped out AIDS very early on. That didn’t happen and will never happen.
> Whatever the case, those states with the most stringent measures also seem to have had the most deaths per capita
I think you may actually not understand the concept of direction of cauality.
Remarkable.
Count on Josh to be unable to understand a true and well formulated sentence.
Frank: “Eventually, your pandemic will be reduced to localized outbreaks that can be stamped out with severe LOCAL measures and local universal testing.”
Where will the localized outbreaks be? Based on current situations, everywhere. Where will the “severe local measures” need to be implemented? Everywhere. Unless you implement severe travel restrictions- like NY, NJ, CT, Washington DC. And if you don’t put political exceptions on your “severe” measures, like DC just did (they mandated a 14-day quarantine for any DC resident traveling to Georgia, then immediately said it didn’t apply to any DC resident who traveled to Georgia Rep. John Lewis. )
Stay at home, unless you want to join the left’s nightly street festivals.
Wear a mask, except in April when the pandemic was peaking.
Abide by the travel restrictions, unless they’re inconvenient to mayor.
Don’t go to a restaurant, unless you want to burn or loot it.
Do not hold funerals, unless politicians want to.
Read how New York “controlled” the virus and Texas didn’t, unless you count the dead.
And be advised European countries “stopped” the virus, unless you include the growing numbers of outbreaks.
dppy6629 wrote: “I just don’t BELIEVE that the strategies you advocate can work in the real world as they have not worked with past epidemics unless the contagiousness was lower.”
Respectfully, I think you are suffering from confirmation bias. The only evidence you can remember is evidence that agrees with your preconceptions. The fundamentals of a pandemic are simple:
1) Coronavirus is transmitted from person-to-person by close contact usually indoors. Reduce the number of contracts and you WILL reduce the average number of new people being infected by each currently infected person. Right?
2) The likelihood of transmission during any contact CAN be made safer by: required quarantine of anyone testing positive, recommending and providing free quarantine and automatic testing to those identified by contact tracers to have been in contact with those who have tested positive, getting testing data to contact tracers within a maximum of 8 hours rather than 2 or more days, requiring face mask or shields, forehead temperature scans to enter schools, workplaces and other public buildings, better air filters and ventilation, hand sanitizer outside every public entrance door, etc. Right?
3) The number of contacts and the safety of contacts determines the future course of the pandemic. Right?
The evidence from European countries and China is overwhelming that effective measures COULD HAVE reduced our new case load by 10-100 fold. Some Asia countries have demonstrated from the beginning of this pandemic that effective measure can contain initial outbreaks. Right?
dpy6629: “One can look at California where they have had a very strict lockdown that essentially continues to this day. Yet cases are growing.”
Total nonsense. On July 14, the BBC reported:
“California has REIMPOSED restrictions on businesses and public spaces amid a spike of coronavirus infections in America’s most populous state.
Governor Gavin Newsom on Monday ordered an immediate halt to all indoor activities at restaurants, bars, entertainment venues, zoos and museums. In the worst-affected counties of the south-western US state, churches, gyms and hairdressers will also close.”
https://www.bbc.com/news/world-us-canada-53399080
California had lifted almost ALL of their restrictions, even on high risk activities such as bars, gyms and indoor dining. Many states began cautious re-opening of sites where contacts were least dangerous in May or early June, but since then – encouraged by the White House – many have abandoned all caution. Even states with Democrat governors were pressured to follow. (At the end of May, I speculated about a worst case scenario of cases doubling every five days, but haven’t done the analysis on the current surge.)
dpy6629 wrote: “And hospitals were never even close to being overwhelmed except possible in NYC. Speaking of this is really scare mongering. Just as the “ventilator crisis” was largely not justified.”
More confirmation bias. Have you forgotten watching the lines of patients waiting to get into NYC hospital emergency rooms at the end of March? NY and other large states began imposing lock downs on March 19 and 20. The earliest time these measures could have influenced the rate of new hospital admissions would have been one to two weeks later. New cases were doubling every 2.5 days in the US in March. There is absolutely no doubt that those restrictions kept NYC area hospitals and probably others from being overrun in April. An exponential increase in new cases will inevitably overrun fixed resources like hospital beds (and professional staff whose numbers have been limited to lower costs). The only thing that can stop it are changing behavior (motivated by fear), public policy, and rising numbers of immune survivors (too slow to have an impact so far by traditional measures. The US went from cases doubling every 2.5 days in March to slightly falling new cases by mid-April because of the restrictions imposed beginning on March 19.
In the past month, haven’t you read the stories about hospital capacity in Florida, Texas, Arizona and New Mexico? This is why these states started restrictions again. This shows again why politics, not economics, is going to prevent us from reaching herd immunity as fast as you would like even in red states. The hardest hit areas today have about 100 new cases/day per 100,000 people – about 1000 days infect everyone before correcting for silent infections and percentage needed to reach herd immunity. In other words, even the hardest hit areas that are worried about hospital capacity are still approaching herd immunity at a painfully slow rate. The Spanish flu arrived in multiple waves over three years (and may never have reached herd immunity) for exactly the same reason.
The ventilator crisis was real until doctors learned that patients with low oxygen levels in their blood could be better managed by having them lie on their stomach rather than by using a ventilator. This has allowed doctors to postpone the drastic step of intubation and greatly reduced the DEMAND for ventilators – which otherwise would have been in short supply.
https://www.jwatch.org/na51855/2020/07/07/prone-positioning-can-help-oxygenation-nonintubated
dpy6629 wrote: “The only case in which your ideal world strategy is worthwhile is if a vaccine that is effective shows up soon. The track record is not very good. But the economic damage is profound.”
I explained why dramatically reducing the number of ill Americans as fast as possible was and remains the strategy that will MINIMIZE economic damage.
dpy6629 writes: “The insanity of this can be seen by asking yourself if you want to lower speed limits to 10 MPH to save 45,000 lives a year. No sane person advocates this approach because public policy is always a balance between lives saved and convenience and freedom.”
And when there is a severe blizzard, we lower the speed limit to 10 mph or even close the roads – for as long as it takes to restore to safety. Some roads in the mountains close for the winter. When this pandemic threatens to exceed the capacity of hospitals, the situation is somewhat analogous to local authorities banning driving BEFORE the worst of a blizzard arrives so the roads aren’t packed with accidents and abandoned cars. The economic cost of letting a big mess develop is much higher than the cost of preventative measures and people can return to normal sooner. Returning to normal is what both you and I want.
jeffnsails850 asks: Will the localized outbreaks be? Based on current situations, everywhere. Where will the “severe local measures” need to be implemented? Everywhere. Unless you implement severe travel restrictions- like NY, NJ, CT, Washington DC.
South Korea reported only 30 new cases of coronavirus yesterday and have never forced businesses to shut down. In less than 24 hours after blood samples are taken, everyone an infected person reported being in contact with is notified. Information from the sick person’s credit card transactions has been used to automatically notify everyone who made credit transactions at the same place and time. South Korea never closed their borders to China or the US, but they certainly have installed an app on every visitor’s cell phone to ensure they obey the quarantine rules and can track everywhere they have gone. Nothing is stopping the US from doing the same, but state and local governments don’t have the money to implement new programs. My county recently added 40 contact tracers, but is still looking to add 150 more (4 months after the need was obvious).
jeffnsails850 wrote: Read how New York “controlled” the virus and Texas didn’t, unless you count the dead.
Insanity! The fraction of people killed per confirmed infection depends on the age of people getting infected. Today vulnerable people all around the country are scared and taking appropriate precautions, but the recent surge has made necessary contacts twice as risky for vulnerable people as in late April, May and early June and 10-fold more risky in Florida. Back in late March when the pandemic was exploding in NYC and nearby areas on the East Coast (because of flights from Europe), the vulnerable weren’t even being advised to wear face masks. Nursing homes weren’t prepare either, especially because infected staff that could be asymptomatic. Treatment and nursing homes have improved. So naturally the death toll in NY was higher in April than in Texas and Florida today (where the hospitals are surprised how many younger people are being admitted).
The most fundamental measure of how effectively various states controlled the pandemic is the change in the number of new cases and deaths AFTER nature of the problem was apparent and control measures had chance to take effect: 4/1 for new infections and 4/15 for deaths. In NY, there were about 7600 new cases/day on 4/1, 10,000 new case (1,000 dying, 10%) at the peak about 4/10 (7 day averaging), less than 1,000 by early June and about 700 today (with about 15 dying, 2%). Today, NY is administering 3.3 tests per 1000 people with a 1% positive rate. Texas, on the other hand “started” dealing with only 500 new cases/day on 4/1, reached 1000 (with 30 dying, 3%) in early April, gradually rose to 1,500 in May and June, and now has spiked above 10,000 in mid-July (with 250 dying, 2.5%). Today, Texas is administering only 2.2 tests/1000 people with a 12.4% positive rate. (Texas has about 50% more people than NY). If NY “controlled” its pandemic as poorly as TX, there would be about 100,000 new cases a day in NY, and almost 10,000 deaths/day! The main reason why so many died in NY is that the initial outbreak was hitting the most vulnerable in NY very hard, especially nursing homes. Today the death rate in NY per infection has improved by a factor of 5, and is slightly lower than in TX (which has shown modest improvement.
jeffnsails850 wrote: And be advised European countries “stopped” the virus, unless you include the growing numbers of outbreaks.
No country or state has permanently stopped the pandemic until herd immunity has been achieved – almost certainly by vaccination. There will be a war against coronavirus until then, but unfortunately no one has told Americans they ARE at war. That is why there are doubts about schools and colleges re-opening this fall and individuals returning to their normal workplaces. We didn’t win this war in the spring like many other nations and we are currently losing. China, Taiwan and South Korea have proven the coronavirus can be controlled for many months without punitive restrictions. New cases are spiking in Spain, but have not reached the levels seen in April, much less double April (as in the US). Cases are not spiking in Italy, Germany or UK, but they remain vulnerable to new spikes because they haven’t improved in since mid-June. If each infected person were infecting only 0.8 new people, new cases would be dropping about 50% per month. IMO, since they are no longer winning, they are vulnerable to a second wave, but at least that second wave will start at least 10-fold below April highs.
Frank –
+1
dpy6629: I wrote an earlier reply that seems to have disappeared.
dpy6629 wrote: “One can look at California where they have had a very strict lockdown that essentially continues to this day.”
Nonsense. California had lifted most of their restrictions by early June, including risky activities such as indoor gyms, dining and bars.
https://www.bbc.com/news/world-us-canada-53399080
dpy6629: “Most experts who I have read seem to believe that more waves are likely in places like Germany. The fundamental problem is human nature.”
Spain has suffered a large rebound, but nothing like the US. Germany, Italy and UK haven’t seen any rebound. South Korea and China have snuffed out significant new outbreaks. China responded to a new outbreak in Wuhan testing most of the city (10 million tests) in 19 days and found 300 asymptomatic patients. They are serious about winning. We run about 10 million tests per month in the entire country (330 million), the results take 2 days or more to come back, contact tracers are in short supply, no one is required to quarantine, etc.
https://www.cbc.ca/news/wuhan-mass-testing-coronavirus-covid-19-1.5597856
dpy6629 wrote: “Whatever the case, those states with the most stringent measures also seem to have had the most deaths per capita.”
Nonsense. The states that imposed the strictest measures were those with the most severe problems at the beginning of April and they have the most cautious citizens today. See this comment: https://judithcurry.com/2020/07/27/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought-update/#comment-922414
dpy6629 wrote: “And hospitals were never even close to being overwhelmed except possible in NYC. Speaking of this is really scare mongering. Just as the “ventilator crisis” was largely not justified.”
Possibly? Remember the long lines waiting to get into NYC hospitals just days after NY imposed its lockdown. What would have happened without that lockdown? The ventilator crisis ended only because doctors discovered that the oxygen levels in many patients improved when they lay on their stomach or other unconventional position. Doctors stopped immediately intubating patients with dangerously low oxygen levels and managed the problem more effectively with repositioning.
dpy6629 wrote: “The only case in which your ideal world strategy is worthwhile is if a vaccine that is effective shows up soon. The track record is not very good.”
Wake up. Fauci testified to Congress in late July that “there’s no question we’ll have a vaccine to fight this coronavirus, saying “it will be when and not if”. He said he’s “cautiously optimistic” that the vaccine will even be available by the end of the year”. A pretty bold statement, but based progress in clinical trials so far, not speculation. How many people can be vaccinated and how fast is the next question. We only need to deal with one strain of coronavirus and it has a proof-reading polymerase (like most viruses for which we have effective vaccines). There are multiple strains of influenza circulation every year and it doesn’t have proof-reading. Neither does HIV.
https://www1.cbn.com/cbnnews/us/2020/june/fauci-expects-vaccine-by-years-end-death-rate-slows-even-as-virus-cases-increase
dpy6629 writes: “But the economic damage is profound. I fully expect the financial system to approach collapse when mass defaults and bankruptcies start happening. The only alternative may be a massive devaluation of currencies which in the past have been ruinous. A whole class of people who have accumulated some moderate wealth will be ruined, many of them retirees.”
Agreed. But as I explained, a modestly more effective effort in over 10 weeks would have reduced our case load 10-fold. There are plenty of things we could be doing that would allow everyone to be returning to work by now and still reducing our case load. South Korea has contained its outbreaks without shutting down many businesses or closing their border:
https://www.npr.org/sections/goatsandsoda/2020/03/26/821688981/how-south-korea-reigned-in-the-outbreak-without-shutting-everything-down
dpy6629 wrote: “The insanity of this can be seen by asking yourself if you want to lower speed limits to 10 MPH to save 45,000 lives a year. No sane person advocates this approach because public policy is always a balance between lives saved and convenience and freedom.”
Nevertheless, during a blizzard we do lower the speed limit to 10 mph or even ban driving completely. In fact, most cities order all non-essential workers home before serious snow starts falling because it takes far longer to clean up the mess without accidents, stuck cars, and abandoned cars jamming the road. If you are vulnerable or need to be in contact with vulnerable family members or work with co-workers with vulnerable family members, flying in a plane, taking public transportation to work, or patronizing indoor gyms, bars, and restaurants when 0.1% of the people around you are infectious is a bit like driving in a blizzard every day. After four months, we are worse off than we were in April, with many people still working from home, and serious doubts that schools and colleges will open and remain open this fall. Many customers are NOT going to return until they feel safe. IMO, we aren’t going to be able to fix our economy without reducing the number of cases dramatically. And our leaders are not going to standby while cases explode and we appropriate herd immunity reasonably quickly – because our hospitals will be overflowing.
Frank, look at where Texas is compared to NY in each of these buckets of statistical data, it offers an opportunity to “re-express” your notes; or be more relevant:
Rate of U.S. coronavirus cases as of August 3, 2020, by state https://www.statista.com/statistics/1109004/coronavirus-covid19-cases-rate-us-americans-by-state/
New York number 4, Texas number 15
Death rates (per 100k) from coronavirus in the United States as of August 3, 2020, by state https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
New York number 2, Texas number 28
Number of deaths from coronavirus (COVID-19) in the United States as of August 3, 2020, by state https://www.statista.com/statistics/1103688/coronavirus-covid19-deaths-us-by-state/
NY number 1 by a large margin, Texas number 8 (and 50% more population)
Average number of people who become infected by an infectious person with COVID-19 in the U.S. as of August 2, 2020, by state https://www.statista.com/statistics/1119412/covid-19-transmission-rate-us-by-state/
Close, but Texans are still spreading the disease at a slightly lower rate than NY.
But Frank says: “If NY “controlled” its pandemic as poorly as TX, there would be about 100,000 new cases a day in NY, and almost 10,000 deaths/day!” An insanely Onion kind of ridiculous.
Frank:
These cases you mention are making us less vulnerable. All your smart countries are remaining vulnerable. We can contain it at a high level at a high cost. Or get past most of the containment at a smaller cost.
That some countries can do something that is the wrong thing is nice. We are better than them and are showing it now. And a bunch of people are criticizing us as they always do.
It’s virus and it will pass through many people. It is smarter than us. And we have to accept that we are vulnerable to it up to its limit. Not ours. Each person not infected is like leaving cans of gasoline around for the next fire. They didn’t burn now.
All these smart countries have cans of gasoline laying all over the place, and are saying, we’re safe. Because we have gasoline can guarders keeping us safe.
jungletrunks | August 3, 2020 at 8:42 am | wrote:
“Frank, look at where Texas is compared to NY in each of these buckets of statistical data, it offers an opportunity to “re-express” your notes; or be more relevant:”
As I explained – and you chose to ignore – in response to a question I judged the success of NY and TX’s efforts to CONTROL the pandemic based on what happened after NY and TX first had a real opportunity to influence what happened. Due to limited testing and asymptomatic infectious people transmitting the virus, the arrival of the pandemic caught us by suprise. The number of cases in the US doubled every 2.5 days in March – increasing 5000-fold. Much of this happened in the NYC area when passengers brought the disease from Europe at a time when we thought the pandemic was confined to Asia. TX escaped this surge by luck, not skill. NY was one of the first states to issue a lockdown order on 3/20, but it was too late. Those who are infected and who show symptoms do so about 5 days after infection and it takes a few more days before they could get tested and a few more days for results to come in. So April 1, was about the earliest time NY had any REAL opportunity to CONTROL the raging pandemic that was ALREADY raging around them. So I measured the success of their attempts to CONTROL/REDUCE the number of new infections using 4//1 as my starting date. On that basis, NY has gotten 10-fold better and TX 10-fold worse. Deaths lag new infections by several weeks. My starting point for NY’s attempts to control deaths was 4/15.
I’m tired of hearing all of the BS about cumulative deaths. The deaths on 4/15 were the result of ignorance and policies in effect just before NY locked down. With a pandemic raging, deaths weren’t going to drop to zero in a few weeks no matter what the state did. On the other hand, TX had many months to prepare for the surge that is hitting them now. Plenty of testing. Knowledge of transmission by asymptomatic people. Recognition of the extreme vulnerability of nursing homes. They’d seen what happened in NY and knew it could happen to them. And they failed to prevent it.
Now, in fairness, part of NY’s reduction in new infections could have been approaching herd immunity. I don’t believe that is what happened, but I can’t prove it.
+1
I wasn’t ignoring you, Frank, I was just providing you a wide angle lens to google through.
NY wasn’t caught by surprise.
Trump shot off a warning flare in January with his travel ban on China; this flare signal was met with, in NY, and by all Leftists, a din of racist cries. Even Fauci, early on, was downplaying the virus threat in the U.S. For well over a month, post China ban, NY officials were trumpeting there was nothing to worry about, go to the theatre, what have you.
The CDC wasn’t cavalier either, Frank. On January 8, the CDC issued an official health advisory about COVID-19. NY ignored it. Or do they not recognize themselves as a primary travel hub for the nation?
What you’re trying to say is that Leftists were too busy playing a political game and got gobsmacked for ignoring science; they were too busy strategizing about how to make Trump look bad. “NY was one of the first states to issue a lockdown order on 3/20”. Trump orders the travel ban with Europe on 3/11.
That Cuomo ordered NY nursing homes to accept COVID patients is hard to ignore, it represents a cavalier attitude towards life. The lack of concern for economic viability is another example. We’ve all seen literal examples of the hard core Left wishing the economy would fail; unless one insists on wearing rose colored glasses.
You conflate Texas efforts of striking a balance between being responsible while maintaining some semblance of commerce to keep the economy from crashing. The general idea to maintain as close to a normal life as possible, yet apply pressure to secure areas when flare-ups occur. A straddle approach, if you will.
The current trend in Dallas:
https://public.tableau.com/profile/cityofdallasdtxinnovationteam#!/vizhome/Book3_15862351183220/DFWRegionalCases
In Houston;
https://www.tmc.edu/coronavirus-updates/tmc-daily-new-covid-19-hospitalizations/
Do these charts look indicative of control efforts one month after the onset of the Texas flare-up now that you can see the trend heading down?
Your slant remains obtuse; it projects.political messaging control, not science based regional COVID-19 control efforts.
>Do these charts look indicative of control efforts one month after the onset of the Texas flare-up now that you can see the trend heading down?
Of course they do. You are still eliding the point Frank made.
> Do these charts look indicative of control efforts one month after the onset of the Texas flare-up now that you can see the trend heading down?
Of course they do.
> I wasn’t ignoring you, Frank, I was just providing you a wide angle lens to google through.
You are still not dealing with the main point Frank was making, despite that he pointed out to you that you had done so. So we conclude that you didn’t ignore. his points but deliberately avoided them because their implications troubled you.
Should we just look at the current rates relative to their peak to conclude that New York has done much better than Texas? That is the logic you are employing.
This is all very tough. There are no clear answers and public officials are stuck with choosing between different sub-optimal choices. The only simply inexcusable choice is denial and lying, which happens on both sides of the political aisle even if it sometimes differs in magnitude and has an impact which is proportional to the power of the decision-makers.
It’s certainly true that New York (city and state) was late in it’s response just as it’s certainly true that Texas should have done better than it has done – particularly given the lead time that it had.
It’s certainly unfortunate that so many people are reflexively tribal in how they filter the relevant information.
Josh, are you Franks sycophant?
You sound like a gurgling little bucket of stool; are you obsessed, or possessed? Wipe your lens first before fulfilling my previous request for wiping, you’re see things that aren’t there. Don’t Mess with Texas; as the saying goes; the stats speak for themselves, their flare-up, then down, is indicative of being proactively involved with mitigating the virus.
trunks –
lol. Still with the scatology, eh? Keep it up. It’s quite edifying.
Jungletrunks: You provided me two links to hospital capacity in two Texas cities that is currently not strained. Nevertheless, hospital capacity in the states currently undergoing a surge has been in the national news. Stop trying to mislead readers. A quick search turns up an article about Austin hospital, whose normal ICU bed had been full and were using surge capacity:
https://www.kvue.com/article/news/health/coronavirus/coronavirus-austin-texas-covid19-update-august-4/269-a316c85c-0ce3-4dcd-b996-51ffb74884d7
South Texas hospital over-capacity and “had adopted a plan to start triaging the sickest patients”:
https://www.motherjones.com/coronavirus-updates/2020/07/starr-county-rio-grande-valley-texas-covid-hospitals-death-panels/
Temporary facilities being set up in two Texas convention centers:
https://www.kxan.com/news/texas-politics/texas-juggles-protective-supplies-space-as-doctors-ration-and-virus-hotspots-linger/
Given adequate testing and all the experience that has been gained in the past few months, TX certainly had far less reason to be surprised by the current surge that NY in March. While Trump halted air travels from China in late January, he didn’t halt air travel from Europe (except the UK) until March 13 (though he issued the order March 11). As it turns out, the pandemic in NY and most of the US came via travelers from Europe. NY was operating blind at this key moment because of the limited testing capacity at that time and the critical role of transmission via asymptomatic people wasn’t recognized. NY issued lockdown orders one week later on March 20. The day Trump halted travel from Europe, NY had 131 new cases and those people had been infected a week or more before. On the same day NY issued a lockdown, there were 2896 new cases – who were being infected about the time Trump stopped travel from Europe. One week later, NY had 7189 new cases, who were being infected about the time the lockdown order was issued. IIRC, those dying from COVID were typically infected an average of 17 days before death. On April 1, 486 New Yorkers died and they were infected around the time Trump halted flights. On April 7, more than 1000 New Yorkers died and they had been infected around the time the lockdown order was issued.
At the peak of the current surge, Texas is experiencing about 200+ deaths per day, still only a fifth the number experienced by NY in early April – those who were being infected when the lockdown order was issued. This is why the NY death toll is 32,000 while TX is approaching 8,000. But NY is losing only about 10/day, so in 100 days TX will surpass the NY death total – unless Governor Abbott takes effective action to slow the pandemic and compensate for a likely increase if schools open. The fundamental problem is that – if you are NOT REDUCING rates steadily you can’t continue to return to normal without risky a surge. Now it will take months of restrictions to prevent TX from surpassing NY. Instead you wrote:
“You conflate Texas efforts of striking a balance between being responsible while maintaining some semblance of commerce to keep the economy from crashing. The general idea to maintain as close to a normal life as possible, yet apply pressure to secure areas when flare-ups occur. A straddle approach, if you will.”
Your “flare up” is costing at least an additional thousand Texas lives a week and that won’t stop by magic. That is hurting the Texas economy. IMO, the only practical strategy is to focus on winning: faster testing, quarantining those you are sick, warning those who have been exposed and helping them quarantine, masks to reduce transmission, banning high risk non-essential activities such as bars and indoor gyms, safer working conditions, etc. It does NOT mean you need to send everyone home. It does mean you do EVERYTHING ELSE possible so that as many people can continue to work and students can return to school without such surges. Other states and other countries are demonstrating that this is possible.
Sound bites of Fauci talking in February were taken out of context. He always warned that an uncontrolled increase in cases would follow if the pandemic got a foothold in the US, but that currently (before March) there was no reason for ordinary citizens to panic.
Hospitals don’t release elderly patients who can’t take care of themselves at home until they have identified a rehabilitation facility that can take them. In our litigious society, nursing homes didn’t want to take in patients recovering from COVID who were no longer believed to be infectious, so it is not surprising that Governor Cuomo needed to order them to do so. Hopefully, Governor Abbott won’t be required to make a similar decision. PCR tests can identify fragments of viral RNA long after a patient is infectious, so the CDC allows medical workers who have had COVID to return to work without testing 10 days after symptoms first appeared and after 1 day with no fever and improving symptoms. The average nursing home has one staff member for every resident. I think and hope that staff members (who could have been asymptomatic) – not recovering hospital patients – introduced COVID into nursing homes. When a lawsuit provides sequencing data to the contrary, I will change my mind. I’m not going to criticize Cuomo because he wasn’t more far-seeing than most other governors and leaders, but each day he failed to fully grasp the onrushing crisis did cost thousands of lives. Governor Abbott’s failure to act as the TX positive test rate rose from 5% to above 10% was far worse.
Jungletrunks writes: “Your slant remains obtuse; it projects.political messaging control, not science based regional COVID-19 control efforts.
It is difficult for any of us to know when our biases are making it difficult for us to see the world clearly. I’m outraged that our country has handled this crisis so poorly and the situation is being falsely presented as a choice between the economy and suppressing the pandemic. I personally hate the propaganda from both political extremes. The fact that I’m here at Judy’s should tell you I’m not addicted to liberal Kool-aid and think for myself. The fact that you didn’t realize that the current surge in Texas is exceeding the capacity of some hospitals suggests that your view of reality could be distorted.
Frank, you’re being petty while trying to buttress a farce.
On the same date as Trump’s China travel ban, on Jan. 31, the administration also declared the coronavirus a public health emergency; Cuomo ignored that too. On Feb. 9, the White House Coronavirus Task Force briefed governors from across the nation at the National Governors’ Association Meeting in Washington; NY’s gov. Cuomo also ignored this. Add these to my prior list.
The particular Texas COVID stats that I previously posted were used because they represent the two most populous metroplexes in Texas, both accounting for nearly one third of the states population.
The example used in your last July 30 article is titled: “South Texas Hospitals Are Overwhelmed by COVID-19”. It targets Starr County’s tiny 29-bed COVID-19 unit as its example. I don’t mock Starr County’s 29-bed stress; but please, Frank, really? The entire Rio Grande Valley population is only roughly 1.3 million.
Your middle August 4th link: “Texas juggles protective supplies, space as doctors ration and virus hotspots linger”. Linger is the operative word here, Frank. I’m certain we’ve already established that Texas had a July “COVID peak”. But Gov. Greg Abbott addressed these particular supply struggles for the areas of need within the same article you posted: “We have abundant supplies to make sure that we will be able to continue to provide PPE to schools, to hospitals, to nursing homes, to testing sites to any operation in the state of Texas”.
Your first articles headline: “Hospital ICU capacity out of ‘surge stage’, but Austin remaining in Stage 4”. Translation of “Out of surge stage” implicitly means declining. Here’s an Austin chart similar to what I posted for Dallas and Houston: https://www.kvue.com/article/news/health/coronavirus/texas-coronavirus-austin-health-update-july-28/269-6d178d74-a683-4e07-a2ad-c8c0565e1f5f Within the same article you post, Austin Health Authority Dr. Mark Escott told the Travis County Commissioners “APH wants to see Austin stay in the Stage Three territory for two weeks before they transition the City into a Stage Three coronavirus response.” According to Escott, the number of new hospital admissions, which had decreased since the middle of July, has flattened out over the past several days. The commissioner is concerned about elderly demographics.
So you’ve cherry picked a few unremarkable headlines, contextually speaking, relating to the backend of Texas’ recent COVID surge. And as part of your politically driven perception continue to brag about NY being one of the earliest states to announce a lock-down; while implicitly, sanctimoniously, disparaging Texas for being behind the curve.
Texas went into lock-down one day before New York, on 3/19. Texas didn’t need to see the same deaths as NY, Frank.
Texas has been far, far less deadly than NY relative to COVID-19, including with its recent surge. Texas has a different strategy for mitigating the virus while attempting to keep the state economically viable.
Let’s review the per capita body count and total hospitalizations in 2021 in relationship to each states economic productivity before continuing on with more of politically centric crow.
Nothing personal, you’re better with science issues.
I don’t buy the Cuomo spin about sending COVID patients to nursing homes either, not only because of the reporting of this article; but this is good enough for now:
https://nypost.com/2020/05/10/cuomo-was-wrong-to-order-nursing-homes-to-accept-coronavirus-patients/
Frank+Cuomo+De Blasio+AOC=clueless
Don, Maria Bartiromo just did a segment on Cuomo+De Blasio. Very little media will report much about NY’s woes. NYC’s upper east side just reported a 286% increase in crime; robberies, shootings, murder.
In a Monday press conference Cuomo was literally begging people to come back to NY: his personal plea, exact words; “I literally talk to people all day long”…”You gotta come back”…”We’ll go to dinner”…”I’ll buy you a drink”. Not to jab NY; I say this out of great concern for the nation, its revenue is crashing. Unfortunately it’s the nation that pays the price for certain states ineptitudes and poor policy decisions. What makes it worse is the sizable numbers within the respective electorates of these states who want these very things to occur for purely ideological, cultish reasons.
jt,
The disingenuous destructive left goons are trying to tear apart the society that has provided the most good for the most people in the history of our little planet. I am headed to the airport in a few minutes off to spread the word. We are going to stop them.
“I say this out of great concern for the nation, its revenue is crashing. Unfortunately it’s the nation that pays the price for certain states ineptitudes and poor policy decisions. What makes it worse is the sizable numbers within the respective electorates of these states who want these very things to occur for purely ideological, cultish reasons”.
Last I checked New York was near the top in donating to the common good.
“Residents in Connecticut, Massachusetts, New Jersey and New York have some of the highest tax bills in the nation. They also pay thousands more in federal taxes than their state receives back in federal funding.
In total, 10 states are so-called donor states, meaning they pay more in taxes to the federal government than they receive back in funding for, say, Medicaid or public education. North Dakota, Illinois, New Hampshire, Washington state, Nebraska and Colorado round out the list”.
https://www.governing.com/week-in-finance/gov-taxpayers-10-states-give-more-feds-than-get-back.html
Cross, forgive me; I mistook the high pitch whirling of your talking point rolodex for a low flying jet.
The tyranny of fuzzy math is a tactical method the Left fully embraces, here you present a recurring talking point theme.
Red states receive 35.75 percent on average of their budgets from the federal government, while blue states receive 30.80 percent. But it’s because blue states’ budgets are far larger, call it bloat. The 10 states in the best fiscal condition are almost all red states. The 10 states with the worst numbers are almost all blue states. Notice I say almost? It’s because I’m not trying to score while using ridiculous talking points. But if you look at the amount of money the federal government gives to states on a per capita basis, blue states get more.
The average taxpayer in blue states does pay a higher per capita income tax than the average taxpayer in red states. But that’s because those states have more rich people. Don’t the Democrats want the rich paying their fair share? I’m sure other Staes would appreciate their residency, in fact they’re indeed moving.
To rectify some of the disparity, Congress passed the Tax Cuts and Jobs Act (TCJA) in 2017. It put a cap of $10,000 on state and local tax deductions (SALT). Without it, rich people in blue states that had bloated, wasteful, high state and local taxes were able to deduct those ridiculously huge tax numbers from their federal taxes, resulting in those states sending far less money to the federal government. One can always count on fuzzy math when it comes to the Left.
franktoo: I’m outraged that our country has handled this crisis so poorly and the situation is being falsely presented as a choice between the economy and suppressing the pandemic.
I think that your rage is misplaced and that there has been a large economic cost to the actions taken by governors in closing down sectors of the economy.
As to the “this country”, do recall that China and WHO supplied misinformation at the start; other countries with high rates of death include Sweden, Chile, Peru, Brazil, Spain, United Kingdom, Belgium, Panama, France, Mexico… . This country is now conducting about 900,000 tests per day, after a slow start.
This country has many vaccines and medicines in development (more than the EU? That I am not fully up to date on) and numerous clinical trials underway.
As to Texas in particular (and CA, AZ, and FL), if the high death rates of the past week continue for 100 days, unlike NY, NJ, and MA, that will certainly be noteworthy. Meanwhile, as in CA, TX has no shortage of hospital beds, but a few local shortages of ICU beds and medical staff.
Back to outrage: CCP and WHO lying at the start? CDC incompetence at the start? FDA foot-dragging? Fauci and Trump telling us simultaneously that we would have few cases? Fauci and Trump telling us simultaneously that HCQ would be worth a try (in Fauci’s case, to give patients hope even though there was no evidence in support of it.) Gov Cuomo ordering nursing homes to admit discharged patients even though the NYC hospitals had surpluses of beds outside their ICUs; after Cuomo and de Blasio deprecated Trump’s travel bans? Fauci praising Cuomo’s lockdown order?
Amazing how many variations of infection rates are going around for different countries and often even in the same country.
Do we rely on illness diagnosis, throat swab testing or bloodstream antibody testing. Different Hemispheres, different seasons and different people.
Herd immunity obviously means different things for different populations depending on their innate infection sensitivity, which could also be due to different strains of the virus.
Did India and Australia get the Mark 2 10 times less dangerous virus?
Did Italy and New York and London and Spain get the bad Wuhan super virus?
Why is New Zealand so safe ( no one wants to go there)?
Do Indians actually take any chloroquine?
Extrapolating panic headlines about Korean and Indian levels of infection does little to help.
Particularly India where as far as I recall they have not done 1 billion tests yet.
The best interpretations will depend on antibody level testing of selected population groups around the world and for the obvious socioeconomic factors will never get it right.
I would estimate that the true yearly prevalence is going to be between 1-10% of most populations. The death rate will be highly skewed to older people for as yet unknown reasons due to how easily and severely they catch it.
It will also be higher in enclosed building complexes like hospitals nursing homes and apartment towers. Away from the epicentres the risk will drop dramatically. Town mouse V Country mouse.
What is the current estimated USA number of infected people anyway 4 million or >1%, or 30 million I.e. < 10%?
Death rate at 150,000 is < 0.05%
1 in 2000.
If you want to know how many cases there are, divide the deaths by the mortality rate- which means the US has 20-30 million cases and the EU more.
Based on the stats, the US has 3.4% mortality rate of reported cases and the EU over 10%. CNN, two days ago, said the president of the US was “obviously wrong” when he said this meant we had a lower mortality rate, but they “reported” this without any evidence at all. They can’t provide any evidence, of course, because that would force them to admit testing was more prevalent in the US than Europe (which they have inaccurately denied), spread was worse in Europe than the US (which they have inaccurately denied) and/or the US better protected vulnerable populations (which they have inaccurately denied.)
One day we’ll see accurate stats. But not before November.
No lessons learned from the Spanish flu (1918-1920)?
George: I did some reading about the 1918-20 Spanish flu and herd immunity and commented at the link below. Three references in the comment below. No reply from Nic so far.
https://judithcurry.com/2020/07/27/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought-update/#comment-922035
The Spanish flu came in three waves in many places and therefore was probably brought to a halt twice well short of herd immunity by fear and public policy. R_0 was about 1.8, so that pandemic likely was easier to bring to a temporary halt well short of herd immunity. Fear was much greater since the death rate was highest between 20 and 45 (due of cytokine storms in that age group).
The lesson from the Spanish Flu is the lesson of all science. One simulation run is never enough to provide good evidence that an approach is appropriate. Analogy can be dangerous as well as helpful.
Too much of this pandemic has been trying to fit flu to coronavirus. They are similar, but not the same. The differences in the way the virus affects a person before it can cause itself a spread is the material issue I think, and we just don’t have a solid handle on that at present.
If we admitted how little we do know, we may get further.
JAMA editorial about clinical trials:
https://jamanetwork.com/journals/jama/fullarticle/2769139?guestAccessKey=439a223c-4cf5-4d63-b221-ae94fcdfc160&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jama&utm_content=olf&utm_term=073120
Observational Cacophony, Randomized Harmony
Confirmation bias? me?
Confirmation bias? They?
This paper is toxic. It makes no mention of randomised clinical trials which have supported the use of HCQ, and cites two major trials which provide the “definitive findings” against its use. These trials are the UK Recovery trial and the European Solidarity trial. The UK Recovery trial was stopped in early June because the investigators found they were killing off patients with the late stage administration of very high dose rates of HCQ to very sick patients. The European Solidarity trial tests of HCQ were stopped a short time afterwards, citing as input the results of the UK Recovery trial.
Below are the conflict of interest disclosures from the paper you cite:-
“Conflict of Interest Disclosures: Dr Califf reported being head of clinical policy and strategy at Verily Life Sciences and Google Health, an adjunct professor of medicine at Duke University and Stanford University, a board member for Cytokinetics, and former commissioner for the FDA. Dr Hernandez reported receipt of grants and personal fees from AstraZeneca, Amgen, Boehringer Ingelheim, Novartis, and Merck, personal fees from Bayer, and grants from Janssen and Verily, as well as being the principal investigator for the Healthcare Worker Exposure & Outcomes Research (HEROES) Program funded by the Patient-Centered Outcomes Research Institute. Dr Landray reported receipt of grants from Boehringer Ingelheim, Novartis, The Medicines Company, Merck, Sharp & Dohme, and UK Biobank and being co–chief investigator for the RECOVERY trial of potential treatments for hospitalized patients with COVID-19, funded by UK Research & Innovation and the National Institute for Health Research (NIHR).”
Note in particular that Martin Landray was one of the two individuals responsible for the UK Discovery trial, which gave 2400mgs frontend loading dose of HCQ (no test of zinc or azithromycin) to very sick patients within the first 24 hours and 3200mgs within the first 48 hours. In an interview with France Soir, he then stated that the lethal dosage rate of HCQ was somewhere around 10 times what they had used, and moreover stated that the dosage used was the same as for amoebic dysentery. https://www.youtube.com/watch?v=31VEJlRyB2c His colleague Professor Horby denied that he had said this.
This led some doctors to infer that he had confused hydroxychloroquine (which is not generally used to treat amoebic dysentery) with hydroxyquinoline.
About 1 in 4 patients in the UK Recovery trial died. This was not a test of early stage treatment. These were already very sick people. They trial lost more patients from the HCQ treatment arm, very probably from the excessive dosage levels, since the increased mortality observed was similar to that observed in the Brazil clinical trial which tested very high dosage levels (@1600mgs pd) of HCQ on very sick patients. The Brazilian doctors are facing criminal charges. The Brazilian medical team published a preprint on 7th April highlighting that they had observed increased mortality from their high dose cohort. The UK Recovery trial went on administering their high dose levels long after the Brazilian data became public. They did however in mid April remove the pharmokinetic calculations from the updated Recovery Report, as well as the Q&A’s related to dose rate.
Now two months after the headline report that HCQ showed no benefit, we are still awaiting the publication of the results.
The above may not be as sinister as it first appears. In late March, however, a number of commenters raised questions about the protocol published for the UK Recovery trial of HCQ, and concluded that it was purposely designed to fail. Forgive me if I do not accept this paper as a simple unbiased assessment of the benefits of RCTs over clinical observation data.
That’s Saddam Hussein approach. Negotiate until the problem goes away.
Kribaez: The linked paper is complaining about “observational studies”, not random assignment clinical studies. The RTC you mentioned above proved that the doses used of HCQ were hurt, not helped patients desperately ill with COVID-19. It didn’t prove that a lower dose isn’t helpful, nor a combination with azithromycin or zinc – but why anyone would want to try that combination when it doesn’t enhance the activity of HCQ in cell culture experiments is a total mystery to me. Zinc (and essential nutrient) competes with magnesium as the counter-ion in thousand of enzymatic reactions involving ATP and other phosphate-containing substrates. The chances of zinc selectively interfering with viral RNA polymerase and at some magic concentration that is not toxic to host cell processes is small.
The paper linked above begins:
“Amid the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, substantial effort is being directed toward mining databases and publishing case series and reports that may provide insights into the epidemiology and clinical management of coronavirus disease 2019 (COVID-19). However, there is growing concern about whether attempts to infer causation about the benefits and risks of potential therapeutics from nonrandomized studies are providing insights that improve clinical knowledge and accelerate the search for needed answers, or whether these reports just add noise, confusion, and false confidence. Most of these studies include a caveat indicating that “randomized clinical trials are needed.” But disclaimers aside, does this approach help make the case for well-designed randomized clinical trials (RCTs) and accelerate their delivery? Or do observational studies reduce the likelihood of a properly designed trial being performed, thereby delaying the discovery of reliable truth?
The authors of this paper are complaining about observational or non-random-assignment studies like the following one I looked into:
https://www.ijidonline.com/article/S1201-9712(20)30534-8/abstract
The Henry Ford Health system reported on their experiences with HCQ, alone and with azithromycin. (Adding azithromycin had no effect.) In this study, doctors prescribed what they thought was best for individual patients and administrators kept track of the results. HCQ provided a 66% reduction in mortality! However, doctors did not to prescribe HCQ to patients with cardiovascular problems, permitting them to report no torsades de pointes, the side effect that harms or even kills patients in other HCQ trials. And since cardiovascular problems are a co-moridity that greatly increases the risk of death for COVID, the group that got HCQ were expected to be more likely to survive whether or not they received HCQ! As it turns out, the group that received HCQ had an average age 5 years young than the group that didn’t. Again, the HCQ group was more likely to survive whether or not they received HCQ! (The authors tried to correct for this problem using a multi-factor analysis, but used groups aged less than and greater than 65. The increase in mortality rises dramatically with age and is poorly described by two such groups.) Worst of all, the HCQ group was twice as likely to have also been given a steroid anti-inflammatory drug. In properly controlled random assignment clinical trials dexamethasone has shown a 30% survival benefit – the biggest improvement seen in any random assignment clinical trial so far. Therefore the HCQ group again would be expected to have a survival advantage even if they didn’t get HCQ! (The benefits of steroid treatment were not statistically significant in a multi-factoral analysis because the treatment and control groups had so many differences and the confidence intervals were wide. So the authors chose not to correct for the beneficial effects of steroids.) These were all problem I personally identified, but there could be others.
Such observational studies can be valuable in deciding whether to invest in a properly-controlled random-assignment clinical trial with HCQ or HCQ + azithromycin or zinc. (Patients with higher zinc in their blood samples might be more likely to benefit from HCQ.) However, Cardiff et al in the paper above are arguing that the only trials that matter today are the properly-controlled random-assignment trials that will provide a definitive answer. In such trials, one decides what patients can be safely treated with HCQ (an “intent-to-treat” group) and then randomly assigns them to get HCQ or a placebo. However, withholding a known effective treatment from a patient in a clinical trial is unethical, making it hard to run a placebo controlled trial.
Franktoo,
Thanks for the comment. You are raising several issues. Let me try to deal with them separately.
Firstly, why zinc? I am agnostic. From the little I have read, zinc has been studied as an antiviral agent or catalyst for other agents for at least fifty years. It is now essential to a number of important antiviral treatments. Importantly, it is associated with multiple, very complex mechanisms, only one of which is inhibition of intracellular transcription for certain types of virus. I do not know whether it is beneficial or not in the treatment of Covid-19. The jury is still out, as far as I am concerned, but I suspect from observed correlatives that, if you are exposed to the virus, it is a good idea not to be deficient in either Vitamin D or zinc. Perhaps in vivo beats in vitro. Here is an abstract from Carlucci et al, which you might want to peruse:-
“As a result of in vitro evidence suggesting zinc sulfate may be efficacious against COVID-19, our hospitals began using zinc sulfate as add-on therapy to hydroxychloroquine and azithromycin. We performed a retrospective observational study to compare hospital outcomes among patients who received hydroxychloroquine and azithromycin plus zinc versus hydroxychloroquine and azithromycin alone. Methods: Data was collected from electronic medical records for all patients being treated with admission dates ranging from March 2, 2020 through April 5, 2020. Initial clinical characteristics on presentation, medications given during the hospitalization, and hospital outcomes were recorded. Patients in the study were excluded if they were treated with other investigational medications. Results: The addition of zinc sulfate did not impact the length of hospitalization, duration of ventilation, or ICU duration. In univariate analyses, zinc sulfate increased the frequency of patients being discharged home, and decreased the need for ventilation, admission to the ICU, and mortality or transfer to hospice for patients who were never admitted to the ICU. After adjusting for the time at which zinc sulfate was added to our protocol, an increased frequency of being discharged home (OR 1.53, 95% CI 1.12-2.09) reduction in mortality or transfer to hospice remained significant (OR 0.449, 95% CI 0.271-0.744). Conclusion: This study provides the first in vivo evidence that zinc sulfate in combination with hydroxychloroquine may play a role in therapeutic management for COVID-19.”
Secondly, you raise good questions about the validity of the Henry Ford study. All retrospective studies are opportunistic, and carry some bias and, very often, confounding co-variation in key variables, something very evident in this instance in the total dataset. You take what you can find. In this instance, I cannot fault the methodology applied by the authors. They used a nested multivariate regression on the total dataset to test for the variables which might be having an effect, and then they did a good job (in fact a quite remarkable job in mathematical terms) of defining two groups with matching propensities, for their final comparison. The three confounding variables which you mention – cardiovascular problems, steroid treatment and age were all matched to two significant figures between the two groups in the matched propensity sets. (Your comment about age dependence applies to the total dataset, I think, unless you have some additional information about age distribution in the matched datasets?) There might indeed be major biases arising from treatment choices in the total pre-matched sets, but the authors seem to have done a very fair job of trying to eliminate these biases in the matched sets. And they still find a significant benefit from HCQ in the matched sets. Is this result definitive proof? No, it is not. It is just more weight added to the positive side in the balance of evidence.
This brings me to the third point you discuss – the need for an RCT, preferably double-blinded against a placebo control group, without which Fauci will not take an aspirin apparently. There are at least three relevant issues to be considered:- risk management, ethics and statistics. Ethics and statistics say that we will not see a valid RCT this year of efficacy of early treatment – at least not in the USA or Europe. When doctors in Europe were invited to support the Solidarity trial of HCQ, many refused. Some stated or wrote publicly that it was because the trial was poorly targeted on late treatment of hospitalised patients already very ill, when there was already evidence that benefits were marginal at best. However, many also made statements (in France, Italy and Spain especially) that they thought that it was unethical to run a RCT which involved giving placebos to known infected patients when early treatment with HCQ had already proven itself on the available evidence to be a safe way of reducing the risk of severe ARDS and death. The trial therefore involved doing harm to patients by withholding beneficial therapy.
Alongside this medical resistance, the statistical problem is also substantial. Somewhere below I did some very simple design calculations to illustrate the participant numbers required for a trial of sufficient power to allow HCQ to prove itself under the assumption that early treatment could halve the number of hospitalisations and deaths. In all areas which have already been hard hit, IFR’s are falling, probably as a result of younger, healthier patients being tested positive. If severe illness is going to affect less than 5% of COVID-19-positive patients, then a participant group of around 1000 people seems like the minimum necessary to obtain any statistical power in comparisons of early treatments. Yet one trial in New York at St Francis Hospital (see reference by James Cross below) has been trying to recruit just 750 people since April and has still not moved into active status. This trial does not include a placebo group. Personally, I would be more inclined to be recruited into this trial than into a trial where I have a 50% chance of receiving a placebo rather than a HCQ treatment – especially knowing that I could not receive any steroids in the control group for fear of biasing the trial results! However, I would be even more inclined to find a doctor willing to prescribe a HCQ/Az/Z combination for the first five days and then, if the worst happens, to transfer me into a hospital where I may be able to receive steroids or alternative hail mary treatment.
There are so many obstacles to a rigorous RCT that I am fairly certain that it not going to happen this year – in the USA or Europe, at least. This then brings me to the risk management question. If the preponderance of evidence suggests that something is beneficial, but it has not yet been fully tested in a definitive RCT, do you wait or do you start applying it? The answer clearly depends on safety concerns. If you believe that the risks of harm can be reduced to a very small probability, by excluding from treatment certain cardiovascular problems, retinopathy and G6PD contraindications, why would you NOT allow doctors the liberty to prescribe?
Kribaez: Personally, I would be more inclined to be recruited into this trial than into a trial where I have a 50% chance of receiving a placebo rather than a HCQ treatment – especially knowing that I could not receive any steroids in the control group for fear of biasing the trial results!
That is interesting, especially the qualification. I would prefer to enroll in a placebo-controlled study with random assignment because I know that it has a higher chance of getting a correct result — but, as you say, only if the HCQ is independent of the other potential confounders.
Without the placebo control, there is no way to tell whether the treatment made a difference. With confounding, the problem of attribution of any apparent effect is present. The ethical argument against placebo control always depends on knowing the probable result of the clinical trial in advance. Otherwise you have no reasoned expectation of which group has been exposed to the higher risk.
Mr. kribaez’s preference for a trial that doesn’t assign patients with a deadly disease to a placebo arm is not half as interesting, as it is sensible.
Repeat attempt to post with some bad words removed.
Confirmation bias? They?
This paper is toxic. It makes no mention of randomised clinical trials which have supported the use of HCQ, and cites two major trials which provide the “definitive findings” against its use. These trials are the UK Recovery trial and the European Solidarity trial. The UK Recovery trial was stopped in early June because the investigators found high mortality in patients after the late stage administration of very high dose rates of HCQ to very sick patients. The European Solidarity trial tests of HCQ were stopped a short time afterwards, citing as input the results of the UK Recovery trial.
Below are the conflict of interest disclosures from the paper you cite:-
“Conflict of Interest Disclosures: Dr Califf reported being head of clinical policy and strategy at Verily Life Sciences and Google Health, an adjunct professor of medicine at Duke University and Stanford University, a board member for Cytokinetics, and former commissioner for the FDA. Dr Hernandez reported receipt of grants and personal fees from AstraZeneca, Amgen, Boehringer Ingelheim, Novartis, and Merck, personal fees from Bayer, and grants from Janssen and Verily, as well as being the principal investigator for the Healthcare Worker Exposure & Outcomes Research (HEROES) Program funded by the Patient-Centered Outcomes Research Institute. Dr Landray reported receipt of grants from Boehringer Ingelheim, Novartis, The Medicines Company, Merck, Sharp & Dohme, and UK Biobank and being co–chief investigator for the RECOVERY trial of potential treatments for hospitalized patients with COVID-19, funded by UK Research & Innovation and the National Institute for Health Research (NIHR).”
Note in particular that Martin Landray was one of the two individuals responsible for the UK Discovery trial, which gave 2400mgs frontend loading dose of HCQ (no test of zinc or azithromycin) to very sick patients within the first 24 hours and 3200mgs within the first 48 hours. In an interview with France Soir, he then stated that the lethal dosage rate of HCQ was somewhere around 10 times what they had used (!), and moreover stated that the dosage used was the same as for amoebic dysentery. https://www.youtube.com/watch?v=31VEJlRyB2c His colleague Professor Horby denied that he had said this.
This led some doctors to infer that he had confused hydroxychloroquine (which is not generally used to treat amoebic dysentery) with hydroxyquinoline.
About 1 in 4 patients in the UK Recovery trial died. This was not a test of early stage treatment. These were already very sick people. They trial lost more patients from the HCQ treatment arm, very probably from the excessive dosage levels, since the increased mortality observed was similar to that observed in the Brazil clinical trial which tested very high dosage levels (@1600mgs pd) of HCQ on very sick patients. The Brazilian doctors are facing criminal charges. The Brazilian medical team published a preprint on 7th April highlighting that they had observed increased mortality from their high dose cohort. The UK Recovery trial went on administering their high dose levels long after the Brazilian data became public. They did however in mid April remove the pharmokinetic calculations from the updated Recovery Report, as well as the Q&A’s related to dose rate.
Now two months after the headline report that HCQ showed no benefit, we are still awaiting the publication of the results.
The above may not be as sinister as it first appears; incompetence cannot be ruled out. In late March, however, a number of commenters raised questions about the protocol published for the UK Recovery trial of HCQ, and concluded that it was purposely designed to fail. Forgive me if I do not accept this paper as a simple unbiased assessment of the benefits of RCTs over clinical observation data.
Matthew,
Watch this space. I have two comments trapped in moderation.
kribaez: Watch this space. I have two comments trapped in moderation.
Got them. Thanks.
I was disappointed by the article, but I put it up anyway to see if it would attract comment.
“noise, confusion, and false confidence” NCFC?
Yes. Generally the skeptics on this forum are all about nitpicking studies and study methodologies but, if the study happens to confirm something they like, many here are ready to jump on board with the conclusions. That goes for most of us (myself included) to one degree or another.
“The benefits of this approach, if well done, are obvious: by sifting potential treatments and measuring outcomes and safety signals, qualified investigators and funding agencies can choose the most promising therapies for testing in rigorous RCTs”.
The widespread consensus in the medical community (and this i where Fauci comes from) is that randomized controlled trials are the only things that are reliable in the end. Fauci, I think, would be ready along with almost everyone else to recommend HCQ or HCQ+ (or probably even disinfectant) is a decent RCT showed value.
James,
Yes, confirmation bias can hit any of us.
This paper by Professor Harvey Risch (downloadable pdf) was written in early May, but published in the American Journal of Epidemiology in late May, unfortunately almost coincident with the fake Lancet paper, which grounded HCQ use. It sets out the (counter)case for not waiting on RCT results. https://academic.oup.com/aje/article/doi/10.1093/aje/kwaa093/5847586
It is now becoming increasingly unlikely that we will see a European or US RCT this year which tests early treatment of COVID-19 with HCQ/Az/Zinc, despite calls since March. Perhaps we will never see one. For some reason, I am reminded of the old song: “There’s a hole in my bucket, dear Liza, dear Liza.”
There are still about a ton of studies underway testing HCQ. If the pandemic does not suddenly end and the anti-HCQ propaganda is not successful in ending HCQ treatments, we could expect that dozens of trials will be completed and results reported:
https://clinicaltrials.gov/ct2/results?cond=covid+19&term=hydroxychloroquine&cntry=&state=&city=&dist=
In the meantime, we have several countries and significant numbers of docs in most countries, who believe from observing HCQ use in clinical practice over the last 6 months, that it works.
What we do know from the results of the trials and retrospective studies we have seen so far is that HCQ is not a deadly drug, as the left loons would have everyone believe to discourage its use, because Orange Man Bad.
kribaez
There is a study underway.
https://clinicaltrials.gov/ct2/show/NCT04370782
Don,
Your list looks impressive, but if you filter the trials, you will find that very few of the US and European trials are actually on target to test early treatment with some combination of HCQ/Az/Z vs a standard care control group, and the few that get close to the target objective have inadequate participant numbers to provide meaningful results.
I commented recently on a paper by Skipper which set out to test the benefits of HCQ as an early treatment. (https://judithcurry.com/2020/07/06/covid-discussion-thread-part-x/#comment-921169). The results showed twice as many hospitalisations and deaths in the control group as in the HCQ-treated group – similar to other trials elsewhere – but this difference failed to achieve statistical significance, and so the result was reported as “no significant difference between the control group and the HCQ group”. There were over 400 participants in this study. The problem was that the total number of people who ended up hospitalised or dead were (only) 15 people, about 3.6% of the participants.
It is interesting to do some design sums on the number of participants required to reach significance with different levels of hospitalisations and deaths, under the assumption that there are always twice as many hospitalisations and deaths in the control group as in the treated group.
If the control group has 10% hospitalisation and deaths, and the HCQ group has 5%, then, with equal cohorts, you would need a participant group of almost 500 people to be able to show statistical significance at 95% confidence.
At 6% and 3% respectively, you would need about 800 participants.
At 4.76% and 2.38% respectively – which is very close to the actual outcome numbers observed in the Skipper study – you would need a participant group of at least 1000 people to be able to show statistical significance at 95% confidence.
In other words, it is very easy to set up early stage treatment RCTs which will fail to show significant benefit – even when there really is a very substantial benefit there. It follows that we will only see “definitive findings” from an RCT when there is a strong will to carry out a rigorous test of sufficient statistical power.
kribaez: In other words, it is very easy to set up early stage treatment RCTs which will fail to show significant benefit – even when there really is a very substantial benefit there. It follows that we will only see “definitive findings” from an RCT when there is a strong will to carry out a rigorous test of sufficient statistical power.
Thank you for the calculations. That was a good post.
What you wrote is quite correct, krib. We may not ever get exactly the trial we want with the protocol we would prefer and of the necessary size to definitively give the thumbs up or thumbs down on HCQ. But the fact remains that there are a ton of trials underway testing HCQ alone and in a variety of combinations against the COVID.
If HCQ has a significant effect on the virus, it seems to me that should show up in some of these trials. Anybody but a TDS suffering left loon should be hopeful that it proves to be useful. It’s going to take strong evidence to overcome the vendetta against HCQ mounted by the TDS crowd, because Orange Man Bad “touted” it.
Maybe after the political season is behind us for this cycle and POTUS The Donald is firmly ensconced in the WH for FOUR MORE YEARS!, HCQ can get a fair shake.
I am getting geared up to hit the road for MAGA, as I did in 2016. Not going to be wasting much time here on pest control of our left loon bozo contingent.
I’ll be back.
PS: Little weasel apparatchik backstabber Fauci declared HCQ dead based on the totally and obvious fake retrospective Lancet study, but he finds the Ford Hospital retrospective that indicated effectiveness for HCQ “flawed” and of no significance:
https://www.detroitnews.com/story/news/local/michigan/2020/07/31/anthony-fauci-henry-ford-health-hydroxychloroquine-study-flawed/5559367002/
James,
The study you reference (NCT04370782) looks very useful. However, it does not test HCQ+ against a randomised control group. It does directly test the relative merits of the inclusion of Azithromycin vs Doxycycline.
To assess the efficacy of HCQ+ from these results will require a comparison of the outcomes against a control group selected post hoc with matched propensity scores. This is known as a retrospective analysis – exactly the same type of analysis carried out by Ford Hospital on 2541 patients. Since Fauci has rejected the results of Ford Hospital as inadequate, it is not obvious to me why he would accept a retrospective analysis on a smaller number of participants.
Paper submitted to NEJM on the Univ. of Minnesota trial that little weasel Fauci cites as a nail in the coffin for HCQ. The paper also discusses “some inaccuracies in the statistical analysis of Boulware et al.”:
https://arxiv.org/ftp/arxiv/papers/2007/2007.09477.pdf
“We conclude their randomized, double-blind, placebo-controlled trial presents statistical evidence, at 99% confidence level, that the treatment of Covid-19 patients with hydroxychloroquine is effective in reducing the appearance of symptoms if used before or right after exposure to the virus.”
“For 0 to 2 days after exposure to virus, the estimated relative reduction in symptomatic outcomes is 72% after 0 days, 48.9% after 1 day and 29.3% after 2 days.”
“We conclude that, when applied as a prophylaxis, it can significantly reduce the relative proportion of symptomatic patients if used from 0 to 2 days after exposure to the virus (71.98% for 0 days, 48.86% for 1 day and 29.33% for 2 days).”
“Moreover, our results show that the elapsed time between the exposure to the virus and the beginning of treatment is vital to the effectiveness of the antiviral use.”
“We expect the treatment will be more effective when applied to patients in the viral replication period, before viral load reaches its peak which occurs around 5 days after symptom onset.”
James –
> Fauci, I think, would be ready along with almost everyone else to recommend HCQ or HCQ+ (or probably even disinfectant) is a decent RCT showed value.
To think otherwise is to believe that there as a very high prevalence of sociopaths walking around in the public health community – an implausibility that doesn’t stop the conspiracy ideologists.
ISTM that unless a model can reproduce the Swedish curve and the German curve, by altering parameters that can be verified from the data (like care home infections) then it is no good at all for prediction.
Pingback: Why Herd Immunity to COVID-19 is Reached Much Earlier Than Thought – Update | US Issues
I commend this interview with Anders Tegnell concerning Sweden’s approach to the CV epidemic to anyone interested in understanding it and the reasons for it: https://unherd.com/2020/07/swedens-anders-tegnell-judge-me-in-a-year/
42% prevalence in this study
https://videocast.nih.gov/watch=38084?jwsource=cl
Also:
–snip–
Mathematicians at the University of Sussex have warned the scientific community, government and the public about the risk of complacency over the level of ‘herd immunity’ required to stem the Covid-19 pandemic.
Some models have previously predicted that ‘herd immunity’ – where enough people have become immune to Covid-19 to stop it from spreading – could be reached with infection levels as low as 20 to 40 per cent. But a new paper from the University of Sussex urges caution to those taking comfort from these figures.
–snip–
http://www.sussex.ac.uk/broadcast/read/52428
–snip–
The contact structure of a population plays an important role in transmission of infection. Many “structured models” capture aspects of the contact structure through an underlying network or a mixing matrix. An important observation in such models, is that once a fraction 1−1/R0 has been infected, the residual susceptible population can no longer sustain an epidemic. A recent observation of some structured models is that this threshold can be crossed with a smaller fraction of infected individuals, because the disease acts like a targeted vaccine, preferentially immunizing higher-risk individuals who play a greater role in transmission. Therefore, a limited “first wave” may leave behind a residual population that cannot support a second wave once interventions are lifted. In this paper, we systematically analyse a number of mean-field models for networks and other structured populations to address issues relevant to the Covid-19 pandemic. In particular, we consider herd-immunity under several scenarios. We confirm that, in networks with high degree heterogeneity, the first wave confers herd-immunity with significantly fewer infections than equivalent models with lower degree heterogeneity. However, if modelling the intervention as a change in the contact network, then this effect might become more subtle. Indeed, modifying the structure can shield highly connected nodes from becoming infected during the first wave and make the second wave more substantial. We confirm this finding by using an age-structured compartmental model parameterised with real data and comparing lockdown periods implemented either as a global scaling of the mixing matrix or age-specific structural changes. We find that results regarding herd immunity levels are strongly dependent on the model, the duration of lockdown and how lockdown is implemented.
–snip–
https://arxiv.org/abs/2007.06975
“However, if modelling the intervention as a change in the contact network, then this effect might become more subtle. Indeed, modifying the structure can shield highly connected nodes from becoming infected during the first wave and make the second wave more substantial.”
Translation: lockdowns and other government interventions may worsen the subsequent outlook for epidemic growth once they end, due to their interfering with the selective immunizing that would normally occur of individuals who are liable to pass the disease onto more people than average.
Yes; it appears to be another harmful side effect of imposing lockdowns, closing schools, etc.
However, it looks like herd immunity may well have been achieved in some major cities (e.g., London, New York), at least, before or despite lockdown.
> Translation: lockdowns and other government interventions may worsen the subsequent outlook for epidemic growth once they end, due to their interfering with the selective immunizing that would normally occur of individuals who are liable to pass the disease onto more people than average.
Why is a translation needed? You basically just repeated what they wrote.
Of course it’s all rather complicated – as the authors of that article spoke about in the other article I excerpted – and which you skipped over in your haste to “translate” what they said into basically what they said:
–snip–
Professor Istvan Kiss, from the School of Mathematical and Physical Sciences at the University of Sussex, said:
“There is a real risk at this stage of the pandemic that people have been lulled into a false sense of security. In the absence of a vaccine, and with the virus still prevalent in the UK, people are still at great risk.
“In our new paper, we have created models which examine how changes in contact networks during lockdown affect the herd immunity level induced by the first wave of the epidemic. We found that if you consider the way patterns of contact change during lockdown, then actually the level at which disease-induced ‘herd immunity’ is reached is higher than the most optimistic estimates we have seen. That’s because, with many of the most vulnerable people rightly protected, a greater proportion of other people need to become immune. Ideally this happens through vaccination rather than infection, of course.
“In the models we studied, where ‘herd immunity’ was achieved at around 40 per cent when lockdown was implemented as a change in the probability of transmission, we found that if changes in contact patterns were used instead, then the level of herd immunity required to halt the spread of the virus increased by between 5 and 10 per cent – up to 45 or 50 per cent.”
“Now that the UK has moved from a nation-wide lockdown to an expected series of local lockdowns, it is critical that those modelling the spread of the disease consider that personal networks are re-activating, and that they calculate how this could lead to individuals connecting to form clusters where super-spreading can occur.
“For that reason, I urge the public to continue to be cautious and observe social distancing rules and take all possible measures to reduce the chance of infection and transmission. At this stage of the pandemic, there is a risk of complacency.
“This pandemic still has a long way to run, and in the absence of a vaccine, we are nowhere near ‘herd immunity’. For example, even though London has seen some of the highest rates of Covid infections, with perhaps nine per cent of the population infected, the vast majority of Londoners are still susceptible to infection.”
Dr Joel Miller from La Trobe University in Melbourne, Australia, who co-authored the study, said:
“Disease-induced ‘herd immunity’ occurs at a lower level of infection than vaccine-induced herd immunity in part because the highly active people get infected early on. The disease is more efficient than the vaccine at reaching the ones who spread infection the most. When control measures shield these key individuals more than others, the ‘benefit’ of disease-induced ‘herd immunity’ is reduced.”
–snip–
And I have already linked to what Joel Miller had to say about the Gomes paper – Why did you have nothing to say about that?
https://threadreaderapp.com/thread/1286934165967892480.html
J:
“Disease-induced ‘herd immunity’ occurs at a lower level of infection than vaccine-induced herd immunity in part because the highly active people get infected early on. The disease is more efficient than the vaccine at reaching the ones who spread infection the most. When control measures shield these key individuals more than others, the ‘benefit’ of disease-induced ‘herd immunity’ is reduced.”
Let’s make some progress. The goal is to get to herd immunity. The costs of not doing that are seen. How many trillions are we at now?
When we hear of cases, and records cases, and unprecedented cases, that’s the network doing what it does. It is the virus living. It does it in nature. The whole planet does it and has been doing it for 100s of millions of years.
The attempts to prevent herd immunity are like trying to stop water from flowing downhill. To stop the rivers from flowing. It’s a virus that moves through our population, period.
It can be modeled as a network that takes the easiest and shortest paths first. Once the easy paths are gone, they’re used up and the virus is left with the longer paths. As long as enough longer passable paths remain, the virus will keep infecting people. The best way to get rid of these longer paths let the virus through them. That leaves the longest difficult paths. Where we hope the virus is finally contained. Delaying the longer paths (not the longest ones) from being used, leaves the most vulnerable longer in that state. Which is another cost.
There is no workable answer that does not include herd immunity. All these unprecedented cases we see are the longer paths being used up. And then there’s the fact we are who we are. We’re tired of this. The Democrats will be folding soon as they try to jump out in front of their new position.
The goal is to get to herd immunity. My goal in eight words. What’s your goal?
Nic Lewis wrote _ Translation: lockdowns and other government interventions may worsen the subsequent outlook for epidemic growth once they end, due to their interfering with the selective immunizing that would normally occur of individuals who are liable to pass the disease onto more people than average.
My translation – – The human body and the human race immune system needs to constantly evolve. The lockdowns, etc retards and delays the needed development of the human immunity system to the long term deteriment of the human race. ( a variation of Nic’s translation)
Nic says:
>Yes; it appears to be another harmful side effect of imposing lockdowns, closing schools, etc.
However, it looks like herd immunity may well have been achieved in some major cities (e.g., London, New York), at least, before or despite lockdown.
————-
Notice how this on the one hand ignores the impact of behavior and assumes that a putative herd immunity in NY results merely from infections, without consideration of changes in behaviors, but at the same time looks a behavior change as a threat to the maintenance of a putative herd immunity.
Notice how it assumes that immunity occurred “despite” shelter in place orders – even as Nic argues that heterogeneity will lower the HIT – despite that obviously, the SIPs will potentially (effectively) remove many people from the chain of transmission.
Notice how Nic effectively implies that a policy centered around protecting vulnerable people long-term is not practical and will result in disaster when they can no longer be protected, and yet has been promoting a policy option based on an unrealistic notion that you can have a ton of infected people walking around and still protect the vulnerable.
I do not trust Tegnell, he has too much to defend, when he states:
“…Sweden is actually more similar to the Netherlands and the UK than it is to other Scandinavian countries; he believes the Swedish counting system for deaths has been more stringent than elsewhere….” is this contrary to the actual observations.
– the outbreak in Norway was greater per. per capita from the beginning of March until restrictions were introduced, Norway and Sweden had approximately the same number of cases per capita, then it exploded in Sweden and fell sharply in Norway (March 16: 1,146 in Sweden and 1,348 in Norway. April 1: 5,320 in Sweden and 4,877 in Norway, April 15: 12,432 in Sweden and 6,797 in Norway) Sweden has about twice as large a population as Norway
– the counting system is identical for Norway, Sweden and Denmark
– all three nations have large concentrations of immigrants in the largest cities living in cramped areas and where infection rates were high
One of the biggest differences, in my opinion, was that Denmark and Norway closed pubs and that people practiced a large degree of voluntary isolation in the important weeks of March and April. To let health workers sit as usual and drink beer until 2 AM at the pubs and then go to work at the nursing homes the next day without any kind of protection and testing is to ask for trouble, it’s not more difficult than that. But for some reason Tegnell does not understand this.
“To let health workers sit as usual and drink beer until 2 AM at the pubs and then go to work at the nursing homes the next day without any kind of protection and testing is to ask for trouble…”
So we have the whole response (applies to the everyone) and we have one driving response. Which are we talking about? Simply protecting the oldest people impacts the death count materially. We should be factoring out nursing home policy. I am sure it’s been done, but not by many pundits. I suppose you don’t distance everybody. You distance the old people from everybody. Old people are New Zealand. For their own good, they are exiled. Which is important. This is for your own good. Stop fighting it.
Ragnaar: “I suppose you don’t distance everybody. You distance the old people from everybody. ”
That’s the crux. The elderly are at the most risk; representing the preponderance of deaths, and also hospitalizations. Besides the safe measures already in place; add extra rigid measures to protect the elderly, then open up the economy. This would be the fastest path to achieve herd immunity, and to minimize death and hospitalizations.
Per CDC most recent data: “The overall cumulative COVID-19-associated hospitalization rate was 130.1 per 100,000; rates were highest in people 65 years of age and older (360.2 per 100,000)”
I’ll add; It was evident early that the elderly were at the highest risk; it makes Cuomo’s insistence that nursing homes accept COVID patients a criminal issue, IMO. NY’s 32k COVID deaths weren’t wide ranging demographically, they were almost all elderly. Officials early on unequivocally knew the elderly were the most vulnerable.
Ragnaar –
You think that sending kids back to school is a must.
And you want to protect old people.
How do you suggest protecting the millions of grandparent primary caregivers for school-aged children, and the millions more who live in the same household with their grandchildren but aren’t primary caregivers?
Also, some 30% of teachers are over 50 and some 1/4 are at serious risk from COVID:
https://www.kff.org/coronavirus-covid-19/issue-brief/how-many-teachers-are-at-risk-of-serious-illness-if-infected-with-coronavirus/
This non-existent, fantasy plan for “protecting the vulnerable” is a cynical handwave – particularly coming from people who routinely call social safety net spending “theft” and a communist redistribution scheme.
> Simply protecting the oldest people…
Thanks for that illustration of binary thinking.
trunks –
I suspect that you don’t understand my views. Just becsuee I criticize Trump and Republicans doesn’t mean I have a binary view.
Typical binary thinking on your part.
There’s building body of evidence that children are not only protected from COVID-19, but they don’t spread the disease. If good caution is added to the mix, masks, etc.; then evidence suggests this is the best of all demonstrably risky paths to take.
What Science Says About Children, COVID-19 and School Reopenings
https://www.factcheck.org/2020/07/what-science-says-about-children-covid-19-and-school-reopenings/
trunks –
> There’s building body of evidence that children are not only protected from COVID-19, but they don’t spread the disease.
This is the beginning of the first quarter-in particular when considering children of different ages:
–snip–
We detected COVID-19 in 11.8% of household contacts; rates were higher for contacts of children than adults. These risks largely reflected transmission in the middle of mitigation and therefore might characterize transmission dynamics during school closure (3). Higher household than nonhousehold detection might partly reflect transmission during social distancing, when family members largely stayed home except to perform essential tasks, possibly creating spread within the household. Clarifying the dynamics of SARS-CoV-2 transmission will help in determining control strategies at the individual and population levels. Studies have increasingly examined transmission within households. Earlier studies on the infection rate for symptomatic household contacts in the United States reported 10.5% (95% CI 2.9%–31.4%), significantly higher than for nonhousehold contacts (4). Recent reports on COVID-19 transmission have estimated higher secondary attack rates among household than nonhousehold contacts. Compiled reports from China, France, and Hong Kong estimated the secondary attack rates for close contacts to be 35% (95% CI 27%–44%) (5). The difference in attack rates for household contacts in different parts of the world may reflect variation in households and country-specific strategies on COVID-19 containment and mitigation. Given the high infection rate within families, personal protective measures should be used at home to reduce the risk for transmission (6). If feasible, cohort isolation outside of hospitals, such as in a Community Treatment Center, might be a viable option for managing household transmission (7).
We also found the highest COVID-19 rate (18.6% [95% CI 14.0%–24.0%]) for household contacts of school-aged children and the lowest (5.3% [95% CI 1.3%–13.7%]) for household contacts of children 0–9 years in the middle of school closure. Despite closure of their schools, these children might have interacted with each other, although we do not have data to support that hypothesis. A contact survey in Wuhan and Shanghai, China, showed that school closure and social distancing significantly reduced the rate of COVID-19 among contacts of school-aged children (8). In the case of seasonal influenza epidemics, the highest secondary attack rate occurs among young children (9). Children who attend day care or school also are at high risk for transmitting respiratory viruses to household members (10). The low detection rate for household contacts of preschool-aged children in South Korea might be attributable to social distancing during these periods. Yet, a recent report from Shenzhen, China, showed that the proportion of infected children increased during the outbreak from 2% to 13%, suggesting the importance of school closure (11). Further evidence, including serologic studies, is needed to evaluate the public health benefit of school closure as part of mitigation strategies.
–snip–
https://wwwnc.cdc.gov/eid/article/26/10/20-1315_article
The article lists limitations, but it is a very large study utilizing a robust system for contact tracing.
Also this:
–snip–
Our analyses suggest children younger than 5 years with mild to moderate COVID-19 have high amounts of SARS-CoV-2 viral RNA in their nasopharynx compared with older children and adults. Our study is limited to detection of viral nucleic acid, rather than infectious virus, although SARS-CoV-2 pediatric studies reported a correlation between higher nucleic acid levels and the ability to culture infectious virus.5 Thus, young children can potentially be important drivers of SARS-CoV-2 spread in the general population, as has been demonstrated with respiratory syncytial virus, where children with high viral loads are more likely to transmit.6 Behavioral habits of young children and close quarters in school and day care settings raise concern for SARS-CoV-2 amplification in this population as public health restrictions are eased. In addition to public health implications, this population will be important for targeting immunization efforts as SARS-CoV-2 vaccines become available.
–snip–
https://jamanetwork.com/journals/jamapediatrics/fullarticle/2768952
I’ll also note re schools – obviously children are not the only people in schools. Opening schools means high connectivity among adults, among whom some 25% are at high risk for severs disease from covid.
Keeping schools closed is obviously very problematic. But it doesn’t serve anyone well to adopt binary thinking to assume that opening schools isn’t high risk especially in communities where there’s a high rate of spread and/or high prevalence of people who are at high risk.
Josh, Generally you can find science that is contradictory to many of your own binarily couched claims, uh, snips. I don’t think there’s time for an IPCC type commission to officially validate propaganda, yet; though media certainly is giving it a go.
As you continue with your frenzied google for brains searches looking for material to buttress your sense of relevance via volume; we would suggest you also keep an eye out for a men’s room icon where you may constructively unload your caché of digested diarrhea, consider this symbolically as the embodiment of a cumulatively necessary data dump, or in colloquial terms, pit stop, or hitting the head. As further comfort, you may find a good nugget that passes the charlatan smell test as your own body of knowledge, certainly intestinal fortitude.
trunks –
Wow. Are you always scatalogically obsessed?
“Obsessed”, interesting choice of words. You’re the one using this site as a dump, Josh. We would appreciate it if you would at least wipe yourself for gods sake.
trunks –
> We would appreciate it if you would at least wipe yourself for gods sake.
Still going with the scatalogically stuff, eh?
Look, you seem like a nice enough fella, but I’d prefer if you keep your fantasies about me in the bathroom to yourself.
“Also, some 30% of teachers are over 50 ”
Retire them so they can keep themselves out of the way, which then frees up jobs for younger people to move into – and for those without work at the younger end to move into the workforce, kickstarting their adult lives.
It’s a win all round. It’s pretty clear from the Covid response that a “dependency ratio” calculated using neoliberal fixed amount of money thinking isn’t correct. We can clearly maintain far more people who are retired in real terms.
Let the young work and go to school. Let older people keep out of the way as they feel appropriate. And other than that let the thing take its course.
Neil, if you live in a state that is not yet under left loon one party rule, don’t let it happen. The left loon public school indoctrinators union will be running the show and they won’t go back to work, until their demands are met. And you still have to pay them:
https://www.dailynews.com/2020/07/14/the-hubris-of-the-teachers-unions-could-backfire/
See how fat and smug they look knowing that their political clout/bribery keeps them safe from the burdens of properly educating our youth. And when they retire with an undeserved lifetime free ride pension, they haunt blogs where decent people want to have discussions without being constantly bombarded by smarmy little left loon propagandists.
MAGA 2020! Clean them out.
Joshua’s comment – “Also, some 30% of teachers are over 50 and some 1/4 are at serious risk from COVID:”
A large pool of the teachers dont want to go back to work since
1) they believe the government should protect them from the dangers of life
2) and get paid with taxpayer’s money at the same time.
Even Sweden shut down secondary schools and had to shut down other schools because of staff shortages and deaths due to the virus. Here in the US MLB with a huge amount of resources is struggling to field teams and play games because of positive tests.
And, of course, on the first day of school in Indiana, parents sent their child with a pending test to school. The test came back positive.
Now
“Officials examined seating charts, and students who had been within 6 feet of their infected classmate for more than 15 minutes won’t be allowed to return to school, Olin told CNN. Their families received phone calls informing them their children must stay out of school for 14 days, he said.”
Students at Indiana school back on campus after classmate sent home with positive Covid-19 test
https://www.cnn.com/2020/08/03/us/indiana-student-covid-positive-school/index.html
Dear Parent/Guardian:
Congratulations! Your child has been selected to participate in an experiment on herd immunity for COVID-19. We anticipate that your child will only become slightly ill, probably nothing more than a slight fever and cough; however, be sure to let us know if your child is unable to breath, is dizzy, or has to go to the emergency room so we can remove his stats from our experiment. Do not anticipate any assistance with medical bills. You may opt out of this honor but don’t expect any help from us in educating your kid.
Thanks,
Your local school board
James Cross’s comment – “Congratulations! Your child has been selected to participate in an experiment on herd immunity for COVID-19.”
I presume you are aware that the human body and the human race needs to constantly update its natural immune system in order to survive. the current approach only retards the needed development of the human immune system. With the current approach, each succeeding virus will become more deadly.
Dear Parent/Guardian:
Since your child is fortunate enough to attend a rural school in a Red district, we know that you are not some feinting daisy. We also realize you have bills to pay and you have a job being productive. So we are happy to let you know, we are ready to teach your child history, math and English this year the same as last school year. Keep up the good work.
Your proud school district
Danger is minimal to students and teachers. CDC says reopen. Pediatricians say re-open. Child psychologists say reopen. POTUS Trump says reopen and the left loons pitched a fit.
Teachers are really smart, just ask them. So they can social distance and wear a mask, no problem. They are robbing the taxpayers so the mask is appropriate, anyway. They shouldn’t be allowed within six feet of students, anyway.
https://www.pasteur.fr/en/press-area/press-documents/covid-19-primary-schools-no-significant-transmission-among-children-students-teachers
“In late April 2020, scientists at the Institut Pasteur, with the support of the Hauts-de-France Regional Health Agency and the Amiens Education Authority, carried out an epidemiological survey on 1,340 people linked to primary schools in Crépy-en-Valois, in the Oise department. Thanks to the cooperation of the people of Crépy-en-Valois, the survey, which made use of serological tests developed by the Institut Pasteur, revealed that the proportion of primary school students infected by the novel coronavirus was 8.8%. Based on some cases of infection detected in the students before the schools closed, it appears that the children did not spread the infection to other students or to teachers or other staff at the schools. The results were published online on pasteur.fr on June 23, 2020.”
Tergnell clearly has an agenda and a selective attitude towards uncertainty:
–snip–
His belief is that, in the final account, the Infection Fatality Rate will be similar to the flu: “somewhere between 0.1% and 0.5% of people getting infected, maybe … And that is not radically different to what we see with the yearly flu.”
–snip–
First, that statement flatly ignores the potential for significant differences in prevalence of serious sequelae from COVID compared to the flu – which is kind of weird coming from the head epidemiologist in Sweden.
Second, it ignores the differences in how the IFR is calculated for the flu and covid.
–snip–
This apparent equivalence of deaths from COVID-19 and seasonal influenza does not match frontline clinical conditions, especially in some hot zones of the pandemic where ventilators have been in short supply and many hospitals have been stretched beyond their limits. The demand on hospital resources during the COVID-19 crisis has not occurred before in the US, even during the worst of influenza seasons. Yet public officials continue to draw comparisons between seasonal influenza and SARS-CoV-2 mortality, often in an attempt to minimize the effects of the unfolding pandemic.
The root of such incorrect comparisons may be a knowledge gap regarding how seasonal influenza and COVID-19 data are publicly reported. The CDC, like many similar disease control agencies around the world, presents seasonal influenza morbidity and mortality not as raw counts but as calculated estimates based on submitted International Classification of Diseases codes.2 Between 2013-2014 and 2018-2019, the reported yearly estimated influenza deaths ranged from 23 000 to 61 000.3 Over that same time period, however, the number of counted influenza deaths was between 3448 and 15 620 yearly.4 On average, the CDC estimates of deaths attributed to influenza were nearly 6 times greater than its reported counted numbers. Conversely, COVID-19 fatalities are at present being counted and reported directly, not estimated. As a result, the more valid comparison would be to compare weekly counts of COVID-19 deaths to weekly counts of seasonal influenza deaths.
–snip–
https://www.healthline.com/health-news/why-covid-19-isnt-the-flu
More on why the comparison is strange coming from Sweden’s head epidemiologist:
–snip–
Experts say there are a number of reasons why COVID-19 is a more serious illness than the seasonal flu.
They point out there’s no vaccine yet for COVID-19 and community-wide immunity hasn’t built up.
COVID-19 is also more infectious than the flu and has a higher death rate.
COVID-19 also has a higher rate of hospitalizations.
–snip–
https://www.healthline.com/health-news/why-covid-19-isnt-the-flu
Joshua
you mention schools being not only used by generally non infectious children, but more vulnerable adults, from teachers to cleaners, lunch servers to janitors.
I made a suggestion back in March that many schools could readily teach outdoors in the spring, summer and autumn, using a series of marquees.
I don’t know if they are the same over there, but here there is a tradition of sturdy and heavy canvas marquees which have a high apex and to which the sides can be rolled up or down as far as you like, thereby providing good ventilation and protection against the elements.
maybe fans would be needed in your hotter states.
however the time is passing as obviously it becomes more problematic as autumn approaches, but it could have provided 5 or 6 months of a useful and stimulating teaching space.
That all assumes the school has a playing field but at present there are many halls also available of various sizes and whilst a hassle to spread classes around its better than children missing six months of education.,
tonyb
https://www.healthline.com/health-news/why-covid-19-isnt-the-flu
More on why the comparison is strange coming from Sweden’s head epidemiologist:
–snip–
Experts say there are a number of reasons why COVID-19 is a more serious illness than the seasonal flu.
They point out there’s no vaccine yet for COVID-19 and community-wide immunity hasn’t built up.
COVID-19 is also more infectious than the flu and has a higher death rate.
COVID-19 also has a higher rate of hospitalizations.
–snip–
https://www.healthline.com/health-news/why-covid-19-isnt-the-flu
Nic: It would have been nice if the interviewer had asked some tougher questions: 1) Based on experience with influenza], “I personally believe that this is a disease we are going to have to learn to live with.” Influenza has never been brought under control because its polymerase lacks proof-reading and resistant strains evolve much more rapidly. And there are so many strains circulating, that the average flu shot (which has antigens for three strains) protects against about 50% of strains that are circulating in the average winter. Experts are hopeful that these problems won’t be nearly a serious with SARS-CoV-2, which has a proof-reading polymerase and only one strain to worry about. Influenza is like tackling SARS-CoV-1, SARS-CoV-2, MERS and the coronaviruses that cause the common cold at the same time. In the case of the Spanish flu, a vaccine against one strain of influenza could have saved many lives in 1919 and 1920. 2) Sweden is more like the Netherlands than its Nordic neighbors???? According to my calculations, cases were doubling every 4.5-5.0 days in March, much slower than in many other countries (2-3 days). I don’t know if the Swedes have better hygiene, less crowded public buildings and transportation, or better indoor ventilation, but transmission was less efficient there. It would be interesting to know if seasonal influenza is lower there too. 3) Mask are likely to spread infections because they will make sick people more likely to interact with others???? 4) No questions asked about success in controlling the spread of coronavirus in China, SK and Taiwan????? 5) No questions about how much safer it is in other Nordic countries than Sweden today. 6) How can the safety of nursing homes in Sweden be as good as in other European countries, when the staff that works in those facilities spends their non-working hours living in the middle of a significantly worse pandemic? 7) No questions about his public apology???
The 42% seropositivity (without reaching herd immunity according to the speaker) in Mosher’s link is in a very isolated inbred community in the Alps (one of the questions asked near the end). There could be less variation in susceptibility and transmissibility in this community than normal.
Franktoo: fair points, however I think it is probably unrealistic to expect a tiny online TV channel to ask tough questions of high profile interviewees, who have little to gain from agreeing to be interviewed. I think the most one can expect from such an interview is to extract the interviewee’s answers to a wide range of questions. Other people can then point out any issues with their answers, as you have done.
I will respond on a few of your points:
1) I don’t actually think you are quite right about flu. I attended a lecture by Prof Gupta a couple of years or so ago at which she explained that the influenza virus’s ability to evade the immune system was actually limited to 5 or so variants in one critical area, so it should be possible to produce a vaccine that was effective against all strains of flu. Her group at Oxford Uni has now developed such a vaccine and recently signed a deal to commerialise it.
Also, so far SARS-Cov-2 has not been under that much selective pressure. Once it comes under such pressure, from a vaccine, it may mutate much more.
2) I agree that there are some differences, but I’m not sure that they are as large as you suggest. According to ECDC data, and restricting calculations to when total weekly cases exceeded 100, in the first few days the week-on-week growth in weekly cases was broadly in the 4 to 5 range for Sweden, Norway, the Netherlands and Ireland. That equates to doubling about every 3 days. After that the growth rate declined substantially in all four countries.
3) What Tegnell suggests is possible. I note that another country with a level-headed government (the Netherlands) has recently decided not to recommend mask wearing by the public. Nor does Norway, I believe.
5) I for one would feel quite safe enough in Sweden today.
6) The overall death rate in Sweden is now down to its 5 year average, so I don’t think excess deaths in nursing homes can be a significant problem any more.
I agree with your point that an isolated, inbred community can be expected to have less population heterogeneity than a country as a whole and that the HIT would therefore by substantialy higher for it.
“3) What Tegnell suggests is possible. I note that another country with a level-headed government (the Netherlands) has recently decided not to recommend mask wearing by the public. Nor does Norway, I believe.”
Nic
I am interested on your thoughts on mask wearing excluding the medical/clinical setting and except in the tightly compacted spaces (mass transit, etc)
Aerosol v droplet transmission
Thanks
> I think it is probably unrealistic to expect a tiny online TV channel to ask tough questions of high profile interviewees
Wow.
Thanks for the reply, Nic.
Masks: I’m pretty mechanical in the thinking about masks. Any mask should be able to block an significant number of droplets. The N95 masks used in hospitals clearly protect against aerosols, but surgical and other masks leak around the edges and possibly 50% of aerosols can pass through (but technology should be improving). I suspect superspreaders produce large amounts of aerosolized virus. Fortunately, a single virus doesn’t produce an infection. In the case of influenza, about a 1000 viruses are needed. They might come in one large droplet or hundreds of aerosol particles, so a mask can increase the amount of time you can be exposed to infectious aerosols without becoming infected. As long as you aren’t stupid enough to infect yourself by transferring material deposited on the outside of the mask with your hands, masks might reduce your chances of infection by at least a factor of 2 and possibly more. From the pandemic point of view, even a 20% reduction in transmission makes a big difference over a month or longer.
I started looking into some of the studies in a meta-analysis claiming masks aren’t effective. In one study, the benefits were statistically significant if the amount of time the mask was worn was considered as a factor, but otherwise were not significant. The meta-analysis which incorporated the results of this paper used the non-significant information in an intent-to-treat analysis: The goals was to see if there were a benefit to a certain POPULATION. Half the people in that population didn’t wear the mask regularly. Therefore masks didn’t produce a statistically significant benefit for this population. Which is the technically correct answer, because dozens of other qualifiers could also be used to select a subpopulation where the intervention worked. (Mask work for men, but not women because their hair gets in the way.) The more useful answer is that masks provided some protection to those who wore them, but compliance was a big problem. Today compliance might be less of an issue, especially if better information were available.
Sweden: I’m glad you would “feel safe in Sweden today”, but that isn’t the real issue. Would you want to live in Sweden for the next year using June’s data with about 10 new cases/day/100,000? If the infected person were capable of transmitting the virus for 10 days and testing was only picking up 1 in 10 infected people, then 1 out of every hundred people you are in contact with could be infected. If you are in contact with only 3 outsiders a day for a month, one of them will be capable of infecting you. And since I have a 90+ year old mother in law who needs help daily, I wouldn’t feel safe in Sweden or anywhere else either. I can be asymptomatic and infect her. I don’t expect the government to destroy our economy or limit your personal freedom to protect my mother-in-law, but when you stop and think about it, a lot of people are in necessary contact with vulnerable people. And after needing to visit the emergency room for influenza last winter, perhaps I’m “graduating” into the vulnerable population myself. One hit on an inhaler and I felt sooooo much better.
I hope you are right about a coming universal flu vaccine, but it isn’t here yet. The CDC says the standard vaccine reduces your chance of getting influenza by about 50%. I don’t know if this is because: a) the vaccine provides protection against only 50% of the influenza viruses circulating in an average year or b) only 50% of patients develop enough antibodies to protect against infection or c) some combination of a) and b). I’m under the impression that a) is the major problem, despite the standard vaccination consisting of four different inactivated flu strains. The information shows that the CDC is constantly refining the mix of inactivated viruses used in vaccine because the influenza polymerase doesn’t have a proof-reading subunit and the viral mutates rapidly. Coronaviral polymerases have a proof-reading subunit and mutate much more slowly.
2019-20 vaccine:
The A(H1N1)pdm09 vaccine component was updated from an A/Michigan/45/2015 (H1N1)pdm09-like virus to an A/Brisbane/02/2018 (H1N1)pdm09-like virus.
The A(H3N2) vaccine component was updated from an A/Singapore/INFIMH-16-0019/2016 A(H3N2)-like virus to an A/Kansas/14/2017 (H3N2)-like virus.
Both B/Victoria and B/Yamagata virus components from the 2018-2019 flu vaccine remain the same for the 2019-2020 flu vaccine.
2018-19 vaccine:
Flu vaccines have been updated to better match circulating viruses [the B/Victoria component was changed and the influenza A(H3N2) component was updated].
2017-18
The overall vaccine effectiveness (VE) of the 2017-2018 flu vaccine against both influenza A and B viruses is estimated to be 40%. This means the flu vaccine reduced a person’s overall risk of having to seek medical care at a doctor’s office for flu illness by 40%. Protection by virus type and subtype was: 25% against A(H3N2), 65% against A(H1N1) and 49% against influenza B viruses.
2016-17 Vaccine
A/California/7/2009 (H1N1)pdm09-like virus,
A/Hong Kong/4801/2014 (H3N2)-like virus and a
B/Brisbane/60/2008-like virus (B/Victoria lineage).
some also got: B/Phuket/3073/2013-like virus (B/Yamagata lineage).
2014-2015 Vaccine:
an A/California/7/2009 (H1N1)pdm09-like virus
an A/Texas/50/2012 (H3N2)-like virus
a B/Massachusetts/2/2012-like virus.
some also got B/Brisbane/60/2008-like virus.
2006-07 Vaccine:
The influenza A (H1) component of the 2006-07 flu vaccine was well matched to circulating influenza A (H1) viruses, which accounted for the majority of influenza viruses tested by CDC. There are two groups of influenza B viruses currently circulating, which are known as the B/Yamagata lineage viruses and the B/Victoria lineage viruses. The 2006-07 vaccine contained a B virus from the B/Victoria lineage and 77% of the viruses tested by CDC were from the B/Victoria lineage. Fifty percent of the influenza B viruses characterized as belonging to the B/Victoria lineage were well matched to the influenza B component of the 2006-07 flu vaccine. In the early months of the season, the majority of influenza A (H3) viruses circulating in the country matched the influenza A (H3N2) component of the 2006–07 vaccine. However, the proportion of H3N2 viruses similar to the H3N2 vaccine component declined as the season progressed. Overall for the 2006-07 season, 24 percent of H3N2 viruses were well matched to the vaccine strain.
“Fortunately, a single virus doesn’t produce an infection. In the case of influenza, about a 1000 viruses are needed. They might come in one large droplet or hundreds of aerosol particles, so a mask can increase the amount of time you can be exposed to infectious aerosols without becoming infected.”
I fear that SARS-CoV-2 requires fewer copies of the virus to produce an infection than the influenza virus. A new article (https://doi.org/10.1101/2020.07.27.20162362) suggests no more than ~300 at most. But that estimate seems, if I’ve read it right, to have been arrived at by assuming that 100% of the exhaled breath of one infected person over 2 1/2 hours – containing ~330 virus copies, was inhaled by each infected person at close quarters at a choir event. That seems to be impossible, as 52 out of 61 people were infected. It looks to me that, if 330 exhaled viruses infected 52 people, only a few viruses are needed to infect most people.
The study also estimates that droplet sizes of 2.5 – 19 microns are most important for infection, and it explains why in high humidity infectivity is far lower. The methods used are quite sophisticated and include used of Large Eddy Simulation, a technique used in simulating cloud etc. behaviour in very high resolution climate models.
Joe
“I am interested on your thoughts on mask wearing excluding the medical/clinical setting and except in the tightly compacted spaces (mass transit, etc)
Aerosol v droplet transmission”
Virus-containing particles in the 2.5-19 micron range appear to be most infectious (https://doi.org/10.1101/2020.07.27.20162362). The aerosol – droplet division is not really binary, but I have seen 50 microns suggested.
Other evidence suggests mainly aerosol transmission: this recent paper (https://www.medrxiv.org/content/10.1101/2020.07.13.20152819v1) found that being taller was associated with greater infection risk, whereas with larger particles being more affected by gravity one would expect droplet transmission to be greater for shorter people.
I’m not a mask expert, but I would expect cloth masks not to be very effective against aerosol transmission. Certainly, I see little advantage, and some disadvantages, in wearing masks in the open air, where transmission appears to be very low. Nor am I convinced that they offer much benefit in uncrowded shops, etc., at least where the exposure time is fairly limited.
>I’m not a mask expert, but I would expect cloth masks not to be very effective against aerosol transmission.
Ah, not “very effective”
Something that is only partially effective on a society-wide scale can have a significant impact.
There seems to be a consensus among people who *are* expert – who actually study the mechanics of how viruses spread – that wearing masks might well provide a significant benefit even if the case isn’t dispositive.
This might be true regardless of whether non-N95 masks are effective against the inhalation of small, aerosolized particles.
There are videos easily available that show that wearing masks affects airflow (reducing the distance of larger particle transmission as well as reducing smaller particle aerosol transmission) when people are breathing, speaking, coughing or sneezing, and I’ve also read some stuff on the potential benefits from masks increasing the moisture levels behind the masks); thus it’s interesting to see people who read a few articles on micron size and then consider themselves sufficiently qualified to offer their advice when asked to do so. Such is the power of motivated reasoning.
Frank –
You might find this interesting:
https://twitter.com/richardneher/status/1289627859854606339
As usual Josh falls for the pseudo-science of colorful fluid dynamics. The literature shows no benefit of masks in a community setting. There is a benefit for health care workers even though compliance is a problem due to side effects like headaches.
I don’t see any rationale or usefulness in arguing against or refusing to wear masks in public. They work to some extent. Period:
https://www.youtube.com/watch?v=XG1Du-GOJs0
If link doesn’t work, it’s titled:
COVID-19 Update 16: Effectiveness of surgical masks for prevention
There are numerous videos of tests of folks talking, coughing, singing that in laser light show the effects on projected nastiness with and without various types of masks. I posted a video of the NYC respiratory doc working day and night in the busiest COVID hospital in the country, who said wear the mask in public, if for no other reason than it keeps you from touching your face. When you get home carefully remove mask, wash hands and you reduce your chances of croaking.
> There is a benefit for health care workers…
Strange how the most simple of concepts escape some people repeatedly if they are appropriately “motivated.”
The point of a health care worker wearing a mask is to prevent the mask-wearer from getting infected. So the benefit to them is basically irrelevant to the question of the benefit from the general public wearing masks.
The purpose of the general public wearing masks is to reduce, on a society-wide scale, the spread of the virus through larger particles traveling longer distances if people aren’t right next to each other, or reducing to some extent the # and distance tracked of aeeosoized particles circulating in places where people might encounter them.
If a mask obstructs airflow to some extent, it could reduce the distance larger and smaller particles travel, and even the number that escape beyond the mask. Increasing humidity behind the mask might have a similar benefit
The related evidence doesn’t seem, as near as I can tell, definitive. That’s life. Sometimes you have to make decisions in the light of imperfect evidence.
They key is to not generalize from imperfect evidence as we see here:
> The literature shows no benefit of masks in a community setting.
Yeah – and Florida has vastly fewer infections vastly more testing than NY.
Remarkable.
Nic: Awesome roughly 5-fold drop in new infections in Sweden in July accompanied by significant drop in positive rate (2-fold?). More than negated rise 2-fold rise in June – which I wrongly earlier said represented the Swedish pandemic going out of control in earlier comments.
I would guess this drop has been too fast to have been caused by approaching herd immunity, but we really can’t say without a new serology survey. If the age of those with new infections has dropped substantially, perhaps the fraction of silent infections began rising in June (or earlier) because the pandemic has been recently propagating among younger healthier people less likely to get tested.
Did anything happen around the end of June in Sweden to cause a change in behavior or public policy?
I’m not aware of any specific change around the end of June in the testing regime or other policy in Sweden. But, as Tegnell said in the interview I linked to, there is huge regional variability in Sweden. You can see that in plots I showed in my article https://judithcurry.com/2020/06/28/the-progress-of-the-covid-19-epidemic-in-sweden-an-analysis/.
I think that dying-down of outbreaks in a few regions (Jönköping, Stockholm, Västra Götaland) may be the main explanation. Those outbreaks were probably in localities where herd immunity had not been achieved (but now has been, presumbably). Even after a country has achieved herd immunity on an overall basis, localised outbreaks can still occur, but they will not spread across the country.
I don’t believe this has been linked here perviously:
–snip–
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Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
View ORCID ProfileStephen M. Kissler1,*, View ORCID ProfileChristine Tedijanto2,*, View ORCID ProfileEdward Goldstein2, View ORCID ProfileYonatan H. Grad1,†,‡, View ORCID ProfileMarc Lipsitch2,†,‡
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Science 22 May 2020:
Vol. 368, Issue 6493, pp. 860-868
DOI: 10.1126/science.abb5793
Article
Figures & Data
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What happens next?
Four months into the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) outbreak, we still do not know enough about postrecovery immune protection and environmental and seasonal influences on transmission to predict transmission dynamics accurately. However, we do know that humans are seasonally afflicted by other, less severe coronaviruses. Kissler et al. used existing data to build a deterministic model of multiyear interactions between existing coronaviruses, with a focus on the United States, and used this to project the potential epidemic dynamics and pressures on critical care capacity over the next 5 years. The long-term dynamics of SARS-CoV-2 strongly depends on immune responses and immune cross-reactions between the coronaviruses, as well as the timing of introduction of the new virus into a population. One scenario is that a resurgence in SARS-CoV-2 could occur as far into the future as 2025.
Science, this issue p. 860
Abstract
It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained because a resurgence in contagion could be possible as late as 2024.
–snip–
https://science.sciencemag.org/content/368/6493/860
Oops. I’ll try that again:
–snip–
Abstract
It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained because a resurgence in contagion could be possible as late as 2024.
–snip–
https://science.sciencemag.org/content/368/6493/860
Here are some other relevant points that Kissler et al. make, which you don’t mention:
“The authors are aware that prolonged distancing, even if intermittent, is likely to have profoundly negative economic, social, and educational consequences.
Our goal in modeling such policies is not to endorse them, but rather to identify likely trajectories of the pandemic under alternative approaches, to identify complementary interventions such as expanding ICU capacity and identifying treatments to reduce ICU demand, and to spur innovative ideas (55) to expand the list of options to bring the pandemic under long-term control.”
“Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022.”
If critical care capacities are not exceeded, reduce social distancing. But cases. Unprecedented cases. Many hot spots. Very bad.
> Here are some other relevant points that Kissler et al. make, which you don’t mention:
Yes, it’s complicated. It’s a balancing act. I’m glad that we agree, and that a blanket argument that shekte in place orders = bad and a restriction of “basic freedoms” is uselessly simplistic.
In ongoing covid19 statistics, cases have dissociated from deaths.
Here in Belgium as an example, the peak of daily cases in April was followed by the peak in daily deaths less than a week later. They followed eachother closely. The same in most countries.
https://ourworldindata.org/coronavirus-data
However now, after reaching a minimum one month ago (end June) daily “cases” have increased an order of magnitude from about 50 to 500 per day, and rising.
However over the same period, daily deaths remain unchanged at less than 10 per day – no increase.
Something has changed. It might be reporting.
It might also be the new strain of covid19, D614G, causing this.
It is more infective – higher r0 – but less severe in health outcome.
Phil –
>In ongoing covid19 statistics, cases have dissociated from deaths.
I think your statement is a bit overly-broad
In the US it seems there has been a sharp increase in deaths even it isn’t as sharp as the increase in cases.
Not surprising that armchair epidemiologists that like to pontificate here were dead wrong when the predicted that the “pandemic is over” and that ejfee would be no increase in deaths because fmdhenknxrese in cases was only due to more testing and/or younger/more asymptomatic people being tested.
That said, those factors do seem to be in play as well as improved treatment to reduce fatality rate. Perhaps similar phenomena in Belgium?
Yes in the US the uptick in cases started a month or so before that in Belgium. And deaths are rising in the US also after 2-3 week lag from cases. This probably lies ahead for Belgium and UK, i.e. will start about now.
Latest on repurposing IL inhibitors:
https://blogs.sciencemag.org/pipeline/archives/2020/07/29/the-latest-repurposing-news
I’m planning to travel (alone) from Belgium to England in about a week’s time, to represent our family at my brother’s wedding. At present this is at least allowed (although there’s a chance UK might quarantine arrivals from Belgium). Any comments on whether this is a good idea or not?
Philip
How do you intend to travel and where is the funeral to be held? Are you needing hotel accommodation or have you family that can put you up as presumably you will be away at least one night?
Tonyb
Tonyb
As you say there is a lot of talk about putting Belgium into our quarantine list.
The warm embrace of government taking care of you. It’s been tried. Didn’t work. You weren’t happy and just complained all the time.
https://twitter.com/joel_c_miller/status/1134082543878320129
https://i.dailymail.co.uk/1s/2020/07/29/12/31325488-8571789-image-a-19_1596020821217.jpg
Outdone by Sweden. Sweden made itself great again. Not us. We have riots and tear down statues. And if that’s not enough, Biden will save us.
Nic Lewis,
Good to see that so far the real world is reflecting your and Gomes predictions. I recently found a criticism of Gomes work and now cannot find the link. The criticism essentially boiled down to “Why doesn’t earlier herd immunity work for the flu?”. To which my initial reaction was this pandemic is not the flu. My later reaction was I don’t actually know that your model doesn’t work for the flu.
Is there any reason do you think that flu would model differently? Of course Ro would be different, possibly no asymptomatic flu cases too but roughly similar to Covid-19 in many ways.
Stephen Anthony,
There are significant differences between COVID-19 and the flu, as well as similarities.
It appears likely that a substantially higher proportion of the population have partial immunity to COVID-19 by virue of previous exposure to other coronaviruses than have such immunity to the influenza virus most prevalent at the time of an epidemic – particularly when that is the first time in living memory that variant has circulated.
Also, SFAIK most flu transmission is by aerosols, which remain in the air for a long time, with the virus remaining viable for up to a few weeks. That being so, heterogeneity in social connectivity may be a less important factor for transmission than for COVID-19.
Also, the high pre-symptomatic infectivity of SARS-COV-2 may make heterogeneity in social connectivity a much more powerful factor in reducing the HIT. Once people feel ill, they are presumably much less likely to go to social functions.
These factors would result the HIT being reduced substantially less by population heterogeneity.
Thanks a lot for your reply. I can see now that a long lived virus outside the host (such as flu) would create different problems for your & Gomes et al’s model.
The context of the lost article was a male epidemiologist being interviewed and it didn’t give a lot of space for Gomes et al’s work. He seemed more concerned with the fact that her paper was not peer reviewed, In the midst of a pandemic where lives will be lost, his attitude seemed to be as useful as a chocolate teapot.
I favor the let it burn forest policies. Fire suppression is an example of trying to beat nature. At low resolution, this is the same thing. We can have a bunch of old trees, and we can clean up all the brush. It costs a lot though, and few want to pay for it.
We have to put out all the fires and we have these heroic people to do so.
A Ponderosa pine forest if left alone will accumulate brush, that then burns without damaging the mature trees. You can walk close to the fire and it’s pretty safe to do so in most cases. I know this because some knowledgeable professor in Montana said so. These fires clear the brush. Accumulated brush when on fire can reach the crown, which does kill the mature trees.
What are the chances that fire will go away? And the forest can live happily ever after? Just as the virus will not go away, as much as we wish it would. Or we have a secret weapon in the works from our able science people.
Everyone is a fire fighter. I’ll shame if you aren’t. Every hour of the day, you are a fire fighter. We are a nation of fire fighters. Our children are fire fighters.
The virus makes us do this. It’s smarter than us.
Clarification: Accumulated brush when on fire can reach the crown, which does kill the mature trees.
Should read:
Excessive accumulated brush resulting from fire suppression when on fire can reach the crown, which does kill the mature trees.
—————-
Left alone, a Ponderosa pine forest rarely has crown fires.
–snip–
Sanjay Gupta and Andrea Kane just ran an extensive front-page CNN article reporting that some residual T-cell immune responses cross-react with SARS-Cov-19, perhaps enough to provide many people with some protection. The article seemed straightforward and reasonable enough until it got to this strangely erroneous statement:
For herd immunity, if indeed we have a very large proportion of the population already being immune in one way or another, through these cellular responses, they can count towards the pool that you need to establish herd immunity. If you have 50% already in a way immune, because of these existing immune responses, then you don’t need 60 to 80%, you need 10 to 30%—you have covered the 50% already.
The source was Prof. John Ioannidis of Stanford Medical School, who since at least March has been making assertions (often challenged by statisticians and epidemiologists) minimizing the dangers of Covid-19.
What’s wrong with his analysis? Let’s look at a very simple and extreme case, just to clarify the logic of the problem, ignoring for now the practical issues, such as that immunity is only partial. Suppose 50% of the population is completely protected without infection, the other 50% is completely vulnerable, the initial reproductive number R0 (the average number of persons infected by each case as the epidemic begins) in a completely vulnerable population would be 4, infection always confers immunity, and our actual population is fully mixed. Then, since 50% of the people encountered by an infectious person would be immune, the R0 in our population would be 50% of 4, i.e. 2 (which is within the range of initial R0 estimates for Covid-19 in whole populations).
From that estimated R0 of 2, the standard estimate of the herd immunity threshold would be (1-1/R0) = 50%. The Ioannidis analysis would then say that, since 50% of the population is already immune, you should correct that estimate by subtracting that 50% from the estimated 50% herd immunity threshold. So you need to achieve only 0% more population immunity to reach herd immunity, meaning you start off with herd immunity and there isn’t an epidemic. With a slightly lower R0, Ioannidis’s analysis would give a negative herd immunity threshold.
That’s mathematically wrong. We got the R0=2 from watching the initial exponential growth in a mixed population, so there is an epidemic. Furthermore, within the vulnerable fraction of the population, the herd immunity threshold will only be achieved when 50% of that subpopulation has been infected. That 50% represents an additional 25% of the whole population beyond those who were immune to start. That’s a lot better than the 50% from applying R0=2 to the whole population, but it’s not 0%. With a R0=5 in the subpopulation, we get R0=2.5 in the whole population, and herd immunity requires 60% immunity in the subpopulation, which translates to 30% additional immune in the whole population, not 10% as in Ioannidis’s analysis. And so on.
In real life, things get a lot more complicated, among other things because of partial mixing of populations with a spectrum of susceptibilities, and because the reproductive number declines as preventive actions are taken and the disease spreads. But before dealing with those complications, one needs to develop equations that give sensible answers under simple assumptions
–snip–
https://statmodeling.stat.columbia.edu/2020/08/03/math-error-in-herd-immunity-calculation-from-cnn-epidemiology-expert/
This looks to be another invalid criticism. The original statement says nothing about calculating R0 and thus they appear to have assumed that R0 is known before the herd immunity threshold is calculated. The criticism is that pre-existing immunity will affect the calculation of the HIT, but its not a criticism of what they said. It’s about how to calculate R0. At best its an additional point which Ioannidis knows perfectly well as its obvious.
David –
I suggest that you go over to Andrew’s and explain their error to them.
LOL.
I tell you what. I’ll post your explanation for how they’re wrong for you. Then you can go over to back it up.
Here David –
https://statmodeling.stat.columbia.edu/2020/08/03/math-error-in-herd-immunity-calculation-from-cnn-epidemiology-expert/#comment-1400206
Because I know you’re shy and wouldn’t want to embarrass a “nothingburger” like Gelman, I went ahead and showed them your correction for you.
I’m sure that Andrew and Michael Weissman and Sander Greenland will be deeply appreciative of your pointing out their error.
He posted your comment and your alleged name over there, dpy. He must not have your address and other personal information. Why Judith doesn’t banish this little slimy twerp is a mystery. What is the matter with you,Judith? Is this OK? He’s done it here, also.
Don –
What an excitable little fella!
David used Andrew’s name here and called him a nothingburger. No problem with that, right? I’m sure David will be happy to go over to Andrew’s blog and straighten them all out, proudly. It’ll happen any minute now.
Don’t worry your little head about it.
Notice how Josh is too illogical to address the issue himself. He has to rely on others who are actually competent even though in this case a little off.
Notice how David doesn’t want to engage with smart people with his criticism, and instead name-calls and takes potshots at them from a distance, and instead attacks defenseless and not very bright people like myself.
Go ahead, David. Go over to Andrew’s to correct their misconceptions. I consider it your duty in the battle against ignorance.
It’s common knowledge who Andrew Gelman is and that the blog you publicize and use in your fake appeals to authority is Gelman’s. It’s also common knowledge that you are a disingenuous nasty little putz and it’s a mystery why Judith doesn’t enforce her thread bombardment rule and kick you to the curb.
When do teachers go back to work?
If Gelman thinks its important, he can comment here. I would take it seriously if he did.
Just to repeat the point, Ioannidis’ and the CNN expert’s statements are correct as they stand assuming that R0 is already known. The point Gelman quotes is an obvious one too, viz., that pre-existing immunity will change R0 from what it would be if everyone was vulnerable to infection.
dpy6629: The original statement says nothing about calculating R0 and thus they appear to have assumed that R0 is known before the herd immunity threshold is calculated.
No. Weissman and Greenland show how a particular R0 would, if known, undermine the argument of the CNN piece. They do that by selecting a value for an illustrative calculation.
Matt, They illustrate how pre-existing immunity would change the calculated value of R0. Once that value is given, HIT can be calculated. At that point, Ioannidis’ statement is of course correct. Those who are already immune count against the HIT total.
Another equally valid way to view this is that the definitions of R0 and HIT are too vague to be useful. If HIT is the percentage who must be immune to achieve an R less than 1, then those with pre-existing immunity must be counted in the HIT percentage. Using this definition, Ioannidis statement is true by definition. In this case, the R0 calculated from initial epidemic curves gives an incorrect value of HIT.
This is just a total tempest in a teapot and not worth the time people have spent on it including me.
I see that another high profile statistician said this about Ioannidis’s calculation (my bold):
Radford Neal says:
August 4, 2020 at 11:47 am
Ioannidis’ calculation is correct if the R0 value being used is that for a completely-susceptible population (with neither immunity from covid-19 infection nor cross-immunity from some other virus, as it’s speculated might actually be the case for 50% of the population). It’s wrong if the R0 value is for a population that has the speculated 50% immunity already.
In practice, the R0 value would have to be estimated, presumably from the spread in the initial outbreaks of covid-19. It is not clear what this R0 value means. If there is no heterogeneity in pre-existing immunity to covid-19 (eg, 50% everywhere), the estimated R0 will be for such a population, and Ioannidis’ calculation would be wrong. But it seems entirely possible that there is heterogeneity in pre-existent immunity, since there will be regional variation in previous viral infections. In that case, it also seems quite possible that the locations of the initial outbreaks of covid-19 were preferentially in the places where there is less pre-existent immunity to covid-19, in which case the R0 estimated from these initial outbreaks might be close to that for a completely-susceptible population, and Ioannidis’ calculation could be close to correct.
https://statmodeling.stat.columbia.edu/2020/08/03/math-error-in-herd-immunity-calculation-from-cnn-epidemiology-expert/#comment-1400747
Looking at the article by Weissman and Greenland makes me really wonder about the motivation of the authors. I cannot see any sort of maths error by Ioannidis. The only way one can deduce an error is by making a very ungenerous assumption about the methodology for calculating the “60 to 80%” – something not discussed by Ioannadis in any shape or form. The authors have chosen to assume that these values were calculated incorrectly by applying an “observed” R0 under the erroneous assumption of 100% susceptible population. Why? Nowhere is this apparent in the Ioannadis statement. If the values are derived correctly under a compatible assumption of 50% susceptibility, then his statement is tautological.
Here is the full extract from the newspaper story:- “For herd immunity, if indeed we have a very large proportion of the population already being immune in one way or another, through these cellular responses, they can count towards the pool that you need to establish herd immunity. If you have 50% already in a way immune, because of these existing immune responses, then you don’t need 60 to 80%, you need 10 to 30% — you have covered the 50% already. The implications of having some pre-existing immunity suggests that maybe you need a small proportion of the population to be impacted before the epidemic wave dies out,” said Dr. John Ioannidis, a professor of medicine and epidemiology and population health at Stanford University.
You note that there is no discussion of where the 60 to 80% comes from. It is a very simple statement and an entirely correct statement if the 60 to 80% has been calculated correctly under the assumption of 50% susceptibility. The authors choose to assume that the values were incorrectly derived under an incompatible assumption.
Suppose that instead of the simple newspaper quote, Ioannidas had prefixed it with the following:-
Let us hypothesise that in a homogeneous, well-mixed population which is 100% susceptible, the observed R0 value of the virus would be 5.0; i.e. on average 5 susceptible people are infected from each infected individual within the infectious period. We would calculate a HIT of 80% ( = 1 – 1/5), applicable to the entire population, under homogeneous assumptions. If, instead, 50% of the population were already immune, then we would expect the observed R0 to be only 2.5 (half of the previous value of 5.0), since, with the same social connectivity and transmissibility of virus, half of the exposed individuals are already naturally immune. This would yield an apparent HIT of 60% (= 1-1/2.5), but this is then applicable only to the 50% susceptible fraction of the population. For the full population, the HIT is then achieved at 50% + 0.6*50% = 80%. Hence, in both hypothetical examples, the proportion of the total population required to reach immunity either by natural resistance or by infection works out to be 80%. The big difference is that in the second case, 50% of the population is already immune, and hence herd immunity is reached when just 30% of the population become infected.
This would then set his quote in context and make his meaning clearer to any analytic, but would probably leave the average reader somewhat bemused. His actual statement, on the other hand, was simple enough for the average reader to grasp the import of having a 50% susceptible population without too much mental strain.
The authors could have written an informative article along the lines:- “It is worth noting that Ioannidis’s statement is true if the 60-80% HIT has been compatibly calculated for a 50% susceptible population, but it can be misinterpreted if it is assumed (by idiots like us) that the range derives from an observed R0 and a calculation based on the assumption of 100% susceptibility.” But no, they want to cry gotcha and argue a maths error.
I must admit that when I wrote the comment immediately above, I had not read through the comments attached to the Weissman and Greenland article. I thought when I read the original article that their ungenerous interpretation of the Ioannidis statement, which led them to declare a maths error, was based on a wilful choice of interpretation and therefore somewhat malicious. However, the comments make it more obvious that it was their inadequacy in basic analytic skills that led them to declare a maths error. Surprisingly, they had genuinely not realised that they were making a choice in asserting how the “60 to 80%” was calculated, and had only considered one fixed option for its derivation.
A reader Carlos Ungil on August 4, 2020 at 4:00 am presented an argument very similar to the one I presented in my comment above. One of the authors, Sander Greenland, has a “Road to Damascus” moment, where he finally realises that there is an entirely valid interpretation of the Ioannadis statement which does NOT imply any maths error on the part of Ioannadis. He responds (to Carlos Ungil) as follows:-
This grudging and ungracious acknowledgement of their error in logic should have been the end of the matter. However, in later comments, Weissman is still unable to “get it” even after his co-author specifically brings the above exchange to his attention, and he (Weissman) continues to argue that there is only one possible interpretation of the derivation of the “60 to 80%”.
Not a lot of glory to share round here.
Indeed, Carlos won the thread as he often does.
kribaez: I must admit that when I wrote the comment immediately above, I had not read through the comments attached to the Weissman and Greenland article.
That is a good post.
Test
Matthew,
Thank you.
Joshua,
“Indeed, Carlos won the thread as he often does.”
If you are now claiming here that you had already realised before my comments that you had in good faith supported something which was fallacious, and then had a change of heart, then it would have been courteous to me and to other readers to make a comment explaining the reason for your withdrawal of support, accompanied in this instance by an apology to dpy6629. It might have saved me many minutes. Given my age, all of my time is incredibly valuable – to me at least.
kribaez –
> If you are now claiming here that you had already realised before my comments that you had in good faith supported something which was fallacious, and then had a change of heart, then it would have been courteous to me and to other readers to make a comment explaining the reason for your withdrawal of support, accompanied in this instance by an apology to dpy6629.
Wow. Here’s what I’m “claiming.” After I posted here, and challenged David to go over to Andrew’s, and posted David’s comment over at Andrew’s, I followed the ensuing convo over there. And from what I could tell, Carlos seemed to have the most insightful take on the subsequent discussion – as nears as I could tell. Carlos often makes very useful and insightful comments – and trying to follow what he writes when the discussion gets technical is what I often try to do.
In fact, after Nic posted his comment above, I had meant to point to Carlos’ comment in particular but I didn’t get to it right away and then forgot. I didn’t see your August 13, 2020 at 5:55 am comment and if I had I may well have pointed to Carlos’ comment at that point.
I’m that sense, I’m not sure that I owe you an apology – as I didn’t read your comment – but it’s kind of funny that you’re taking me to task given that I meant to point to Carlos’ comment w/o reading your earlier comment.
As for an apology to David,…I’m not sure that one is in order: I read Carlos’ conclusion as conditional and so tid Carlos is correct then the correctness of Ioannidis would be conditional (and the criticism of him would be in error for not recognizing the conditionality). To the extent that David’s pronouncement on the correctness of Ioannidis’ was conditional as well, then I offer an apology.
And on top of that I will acknowledge that I displayed childish behavior above. David regularly insults me in his comments. To my recollection he has never apologized for that, and in fact he often complains about ad homs even as he regularly insults me and seeks to discredit my arguments by attacking me (such as saying my arguments should be dismissed because I’m not a scientist), or my character, or my political identity, blah, blah. And while that might be relevant to how I reflexively engaged in childishness, it isn’t a justification for acting childishly on my part. Acting like a child is acting like a child. The only person responsible for that is me.
Actually my main issue with Josh is that he clutters comment threads with very long, repetitious, and usually evidence free comments. When evidence is cited, it is usually from the mainstream media such as the New York Times. He should read Bari Weiss’ resignation letter which says that the Times no longer does journalism. It casts every story to further intersectionality narratives.
He also is ethically challenged. A few years ago he went on the war path to get Judith to change her “biased and motivated reasoning” and was put on permanent moderation for it. The arrogance of an anonymous non-scientist internet persona to judge an imminent scientist’s reasoning with no real specifics is breathtaking. He tried to do the same thing to me earlier this spring. This is classic mind reading behavior, and is unethical for those in the “helping” professions. He also likes to post out of context comments on other blogs to find support for his positions. This instance is just the latest. He even tries to get others to do this dirty work for him.
A word of adult advice for Josh. Cut the unethical behavior. Before commenting ask yourself if your comment is relevant and has more than feelings behind it. Then reduce its length by a factor of 10. You will find that the exasperated responses will be much more moderate and useful for everyone involved.
Just to summarize and wrap this up. This is a really silly phony controversy about an off the cuff statement.
If herd immunity threshold is defined as the percent who must be immune for R to drop below 1, then those who are already immune do count towards the HIT, just as Ioannidis said.
If there is pre-existing immunity, then estimating R from the early epidemic data and then calculating HIT will not give the same HIT as defined above.
Aside from the math error, we really have no idea if even the 50% is a valid number. Nobody knows how prevalent T cell immunity is or how protective it is. It probably declines dramatically with age so may only be of value for people in their teens and twenties.
Coronavirus Immunity: How Does Your Age Play a Factor?
Certain key immune cells — B cells and T cells, which are the virus fighters — become fewer in number with age.
A 2018 study reviewed in the journal Nutrients showed that basic nutrients like vitamins A, C, D, E and the B vitamins, along with folic acid, iron, selenium and zinc, are essential for “immunocompetence,” with deficiencies causing lower T cell production and an inability to resolve inflammation.
– AARP
Let’s argue about masks instead.
Calm
Research has shown that unregulated stress can accelerate immunosenescence.
I was right. Stay calm. Don’t riot. Don’t topple statues and reopen old wounds. The Buddists are kicking our butts.
Ragnaar- your comments regarding declining immunity with age makes sense, though it seems slightly inconsistent with other flu viruses where the death rate is more evenly distributed among all ages whereas covid death rate seems to be heavily skewed to the elderly. That being said, there was some discussion/thought that the oral polio vaccine may have some cross immunity with covid. However the oral polio vaccine was not available until approximately 1961 or 1962 such that the 70 + year olds didnt get the vaccine until their late teens or early 20’s , with the suspected possibility that they never really developed immunity. The implication is that the body’s maturing needs to occur by certain points in time to avoid retardation in various body functions, ie crawling, walking talking, puberty, etc
That being said, the human body and the human race needs to constantly update / improve their immune system. My concern is the current policy is retarding and delaying the needed development / evolution of our immune system to the long term detriment of the human race.
Thoughts
Joshua: https://statmodeling.stat.columbia.edu/2020/08/03/math-error-in-herd-immunity-calculation-from-cnn-epidemiology-expert/
Thank you for the link. It is worthwhile to read the main article; and to read the commentaries and rejoinders.
Everybody is forced to make conjectures about unknown quantities in order to answer the question: What might be happening, and what might happen next? OK, two questions. The biggest mistake might be the belief that one’s favorite conjecture is actually true, given that everything that might be knowable is poorly estimated.
The CNN piece is not based on the most recent evidence, but the conjectural arguments are unaffected because they are obvious conjectures.
Don –
Time to add yet another member of the Trump crew to the TDS list. I know it’s getting quite long (Sessions, Preibus, Scaramucci, Kelly, Bannon, McMaster, Bolton, Potter, Short, Taylor, Cohn, Omarosa, Christy, Hassett, Shulkin, Tillerson, Mattis to name just a few) but I’m sure you’ll have enough hate left to throw some his way as well. Maybe you can just add a “and Goroir too” every time you insult Fauci, to make it easier?
–snip–
The White House coronavirus task force member charged with coordinating the U.S. testing effort said Sunday that the nation needs to “move on” from the debate over hydroxychloroquine, a drug President Donald Trump has promoted as a COVID-19 treatment even though there is no clear evidence it is effective.
It’s being used all over the world, including in the U.S., by doctors treating actual patients, who believe it is effective. There is nothing that is proven to be effective, by any measure other than one or two marginally signicicant clinical trials. Why tf should we move on, because babbling flip flopping apparatchiks who haven’t given good consistent advice say so? Isn’t little weasel Fauci the clown who said the VERY FAKE RETRACTED Lancet study put the HCQ issue to rest? Pathetic. And you should be kicked back to kenny’s blog.
Don –
> Why tf should we move on…
I guess he has his reasons…
… or it’s TDS.
I will help you, dummy. It is not Fauci’s job to determine what drugs are suitable for FDA approval. There are still a gazillion trials of HCQ ongoing. It is still widely used against COVID 19 throughout the world. Several countries rely on it as a part of the standard of care.
The one thing that has been proven by trials and clinical usage up to now is that it is not the killer drug that left loons portrayed it to be, just after Trump “touted” it. It’s safe when properly dosed and that a fact jack. Period.
Fauci declared HCQ dead based on a BLATANTLY FAKE trial that was reluctantly retracted by the Lancet fake TDS editor. It only got by him in the first place, because he is willfully blinded by TDS.
There is politically motivated campaign to squash a drug that a hella lot of doctors are using against a deadly pandemic with no effective cure and you are a snide and nasty part of it.
Joshua: The White House coronavirus task force member charged with coordinating the U.S. testing effort said Sunday that the nation needs to “move on” from the debate over hydroxychloroquine,
The phrase “move on” is totally meaningless here. “It could mean stop quarreling and let the doctors use their own best judgment until research can produce a clear and convincing result.”
Whether Trump is for it or against it is irrelevant at this point.
Are you claiming that Fauci is not and hasn’t been trying to put the kibosh on HCQ? Seriously.
“Whether Trump is for it or against it is irrelevant at this point.”
Very naive.
Brett Giroir might be interested in this recent Italian study which supports the findings of the Ford Hospital study. https://www.ijidonline.com/article/S1201-9712(20)30600-7/fulltext
Don –
> and you are a snide and nasty part of it.
Yeah. The massive reach of my anonymous blog comments is resulting in millions of deaths, if not trillions.
So does Goroir have TDS also? You avoided my question. I think you now have to add Birx as well since she also said that our response to the pandemic hasn’t been “perfect” as your cult leader decrees.
Just for the record, I’m not sure why they just wouldn’t say that HCQ shouldn’t be used outside of clinical supervision, except that they must think that it’s likely to be used irresponsibly.
The problem there is that they may not realize that whenever they discourage its use, it’s only likely to increase its use by cult members who would happily sacrifice in any way if they think it might please their dear leader.
I didn’t say you were a significant part of it. You are not a significant part of anything. You are a loudly buzzing anonymous nasty mosquito. Nothing more. I hope that’s clear now.
Don Monfort: You are a loudly buzzing anonymous nasty mosquito.
Like you he occasionally posts links to worthwhile reads.
But mostly he’s a loudly buzzing anonymous nasty mosquito with a left loon ax to grind. If they prevail, your country is toast. But if you find posting a few links you find interesting redemption for the left loonery, whatever. He’s here to show his imagined moral and intellectual superiority over guys like you, matt.
https://nypost.com/2016/06/09/science-says-liberal-beliefs-are-linked-to-pyschotic-traits/?utm_source=twitter_sitebuttons&utm_medium=site%20buttons&utm_campaign=site%20buttons
Who knew. Explains quite a lot actually. In this case, anecdotal evidence and scientific evidence converge big time.
Don Monfort: He’s here to show his imagined moral and intellectual superiority over guys like you, matt.
That’s not unique. “Show” to whom? Readers can judge.
more on the role of colds in promoting T-cells effective against SARS CoV-2:
https://www.nature.com/articles/s41586-020-2598-9
Here, we investigated SARS-CoV-2 spike glycoprotein (S)-reactive CD4+ T cells in peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors (HD).
Selection: To this end, we designed two peptide pools (15 amino acids
(aa), 11 aa overlaps) spanning the entire S that comprised different
amounts of putative MHC-II epitopes based on identified epitopes in
SARS-CoV11–13 (Fig. 1a). SARS-CoV-2 S peptide pool PepMixTM 1 (henceforth:
S-I) spans the N-terminal part (aa residues 1-643) including 21
predicted SARS-CoV MHC-II epitopes (Fig. 1a, Extended Data Fig. 1,
Extended Data Table 1). The second peptide pool PepMixTM 2 (S-II) covered
the C-terminal portion (amino acid residues 633-1273) including
13 predicted SARS-CoV MHC-II epitopes (Fig. 1a, Extended Data Fig. 1,
Extended Data Table 1). The peptides of the receptor-binding domain
(RBD) in the subunit S1, which represents a major target of neutralizing
antibodies, are included in S-I18,19.
For antigen-specific stimulation, PBMC from patients and HD (see
patient and HD characteristics: Table 1, Extended Data Table 2 and 3)
were stimulated for 16 hours with S-I and S-II peptide pools, respectively.
Antigen-reactive CD4+ T cells were identified by co-expression of 4-1BB
and CD40L, which allows for sensitive detection of S-reactive CD4+
T cells re-activated by TCR engagement ex vivo20–22 (Fig. 2a, Extended
Data Fig. 2, and Supplementary File). In 12 (67%) and 15 (83%) of 18
patients we detected CD4+ T cells reacting against the S-I and the S-II
peptide pool, respectively (Fig. 2b, d, e). Most COVID-19 patients with
critical disease exhibited no reactivity to S-I (Extended Data Fig. 3).
Remarkably, S-II-reactive CD4+ T cells, albeit at slightly lower frequencies
compared with patients, could also be detected in 24 of 68 HD (35%),
henceforth referred to as reactive healthy donors (RHD) (Fig. 2c, d, e).
S-I-reactive CD4+ T cells could only be detected in 6 out of the 24 RHD,
i.e. in 5.8% of all HD (Fig. 2d, e). All HD were negative for IgG antibodies
specific for S subunit 1 (S1) in contrast to patients (Fig. 2f). We further
ruled out early SARS-CoV-2 infection at initial sampling by 1) direct PCR
standard diagnosis in 10 RHD (data not shown), 2) serological testing
(Fig. 2f) and 3) by repeated serological testing at least 28 days later for
65 of 68 HD (Extended Data Fig. 4).
Thanks a lot for your reply. I can see now that a long lived virus outside the host (such as flu) would create different problems for your & Gomes et al’s model.
The context of the lost article was a male epidemiologist being interviewed and it didn’t give a lot of space for Gomes et al’s work. He seemed more concerned with the fact that her paper was not peer reviewed, In the midst of a pandemic where lives will be lost, his attitude seemed to be as useful as a chocolate teapot.
https://issues.org/covid-19-and-the-futility-of-control-in-the-modern-world/
COVID-19 and the Futility of Control in the Modern World
“Just as a hammer can condition its holder to see every problem as a nail, so unfolding forms of modernity around the world are ironically enslaved by their perennial aspirations to control. This is perhaps why the massive challenge of climate disruption is currently addressed in terms of “stabilizing global climate” by controlling the average temperature of the entire planet, an extraordinary conceit.”
Government at almost every level, sucked with the virus. There are many things we can’t control. Yet we keep trying. Fails: Police, schools, science, all of the Federal government, over half of the State governments, almost all of the big city mayors.
Ragnaar: COVID-19 and the Futility of Control in the Modern World
That’s silly. There is every reason to think that at least one of the vaccines now being tested will be helpful in controlling the pandemic.
Why do you include science among the “fails”? Is it too slow for you?
Thank you. The first thing is the confusing messages we got and get from science. The idea that science has an answer that includes shutting down economies I think we can say is wrong. And science has to reach a compromise with economics in this case. What’s wrong with global warming science? What’s wrong with the this science is similar. Science has been wrong many times and did not lead this time. It failed us. I can accept that and call for no changes. More science in this case, would not have saved us. I said elsewhere, we are what made us great. Our science recently is trying to make us not great. Another example of that is the renewables scam. We don’t need to go back to past. We need to acknowledge that some things cannot be controlled. It’s chaos. We are not puppets. It’s too complicated. The answer is the individual. The primary thing that makes us great. We don’t give that up. Like some failed Western European has been of a country.
Ragnaar: Science has been wrong many times and did not lead this time. It failed us.
Science has responded faster to this nearly new threat faster than to any other new infectious agent that I know of; getting 4 vaccines into clinical trials this soon is a major success.
As a martial example, consider the Battle of the Coral Sea, May 1942; it was tactically a loss for the US, but hardly a demonstration that aircraft carriers were a failed response to the new naval threat. Or if you like sports, this is early innings yet; or early 4th quarter of KC Chiefs vs anybody you might name (49’ers?)
.
“Whatever futures may struggle into being, the present pandemic suggests that they will likely turn out better if shaped to resist this failing reflex of control.”
“In the process, can democracy be imagined not as a codified managerial procedure, but as multiple continual struggles for access by the least powerful to capacities for challenging power whose legitimacy depends on the promise of control?”
It’s about control. And science as an instrument of that. They grab the science and use it to assume control. And they are government. So they aren’t very good at it.
So they are going to fix this pandemic. But they need control to do so. What other tools do they have? They were going to fix the climate. They didn’t. I see that they still want control of resources as represented by the amount of deployed renewables.
They assumed control of our economy, and it was a trainwreck. We are fortunate that it is resilient. And there aren’t any better places to put your money.
I don’t care how much they want to fix things and how much people want them to unicorn fix things, they aren’t very good at it.
No way, no how was the Battle of the Coral Sea a defeat for the U.S. The imperative was to stop the Japs (that’s what they were called then) from taking Port Moresby. Mission accomplished.
The U.S.N. lost one fleet carrier, but damaged two IJN carriers enough to prevent them from being able to take part in the Battle of Midway. Their battle strength would have been 6 fleet carriers, to our 3. As everyone knows, Midway turned the tide. We stomped their butts real good and they never recovered.
Don Monfort: No way, no how was the Battle of the Coral Sea a defeat for the U.S.
My phrase was ‘tactically a loss”. The US lost more planes, pilots, and ships, but the damaged US carrier was returned to combat more quickly than the damaged Japanese carrier (because of the naval facility and manpower at Pearl Harbor), indeed in time for the decisive Battle of Midway.
Congress was at the time debating whether to fund more carriers, a decision supported by the Battle of Midway.
My whole point was that a “tactical setback” (e.g. failures of HCQ clinical trials to produce decisive results) is not a “defeat”.
OK, you can ignore the fact that the reason the USN was in the Coral Sea was to prevent the IJN from taking Port Moresby. Do you think that wasn’t important? And there is no way in hell that the United States was not going to produce carriers in over-abundance for the war in the Pacific, after the Pearl Harbor lesson.
We lost a rook and four pawns, they lost a knight and five pawns with two rooks put out of action. They were prevented from taking Port Moresby and their fleet minus two of the planned six fleet carriers got stomped at Midway. Some naive nimrod armchair historians might call Coral Sea a tactical defeat, but we know better.
PS: The Japs lost more planes and pilots. The Zuikaku was put out of action, substantially because they lost a lot of planes and aircrew.
You like links:
https://www.navytimes.com/news/your-navy/2019/05/03/what-if-the-japanese-had-won-the-battle-of-the-coral-sea/
Alex Berenson: “There Are Good, Epidemiological Reasons That Lockdowns Don’t Work”
https://www.realclearpolitics.com/video/2020/08/05/alex_berenson_there_are_good_epidemiological_reasons_that_lockdowns_dont_work.html
I’d call it a science fail.
“”There are good, epidemiological reasons that lockdowns don’t work,” he told Carlson Tuesday, “which is why, for 15 years, experts on pandemics said this was not a good idea and all of a sudden in March they threw out everything they been saying.””
The science today. Look we did this, and Sweden is bad. Facist countries are kicking our butts with behavior modifications.
We flattened the curve. Remember that? It was a panic. That’s the science today.
Say I believe the 15 years thing above. Slowly. I’ll go with the 15 years thing until something better comes along. Science is not to panic.
Science today is the gotcha question, How many deaths are acceptable? Our politicians failed at science, and the scientists who ought to know better failed. The reason we listen to scientists is what?
We are fine. It’s time to get back to work. People die. It’s part of life.
Don Monfort: OK, you can ignore the fact that the reason the USN was in the Coral Sea was to prevent the IJN from taking Port Moresby. Do you think that wasn’t important?
If you don’t like the Battle of the Coral Sea as a “tactical loss”, consider the First Battle of Savo Island. Or the Prussian setback at Quatre Bras just before their re-emergence at the Battle of Waterloo.
>Government at almost every level, sucked with the virus. There are many things we can’t control. Yet we keep trying. Fails: Police, schools, science, all of the Federal government, over half of the State governments, almost all of the big city mayors.
I love how the set of folks who hate them some gubment ’cause all the failures, tends to overlap with the set of folks who promote the message of Pinker et al. who talk about how much things are getting better.
Less violence, less hunger, less crime, more equal rights, less discrimination, rising standard of living, scientific advancement in many, many realms, more access to speech, longer life expectancy, lower infant mortality, more agency for more people all across the planet – all contemporaneous with “more government” that “fails.”
Ah, for the good ol’ days when fewer people had more disproportionate power, I love the binary thinking. Thanks for the quote, Ragnaar.
If only we could go back to Shangri-la when people could build statues honoring people who fought to preserve the institution of slavery – things would be so much better!!!!!! Make ‘Merica Great Again!!!!!
All those good things you mention. Capitalism. What didn’t fail in the Godzilla of a pandemic? Amazon. Businesses free of the new restrictions for the most part. Wal-mart and Target did not fail. Hardware stores in MN anyway. You run a country for the 1% of the time you have to do something. This was one of those times. We failed. You put these idiots in charge, and see what happens? Capitalism. Dollars. Greed. My money. That’s what’s good. Let’s try that.
Correlation does not imply causation. We do know that socialism and communism have been human rights disasters wherever they have been tried and the ideology actually calls for elimination of freedom.
Where is the country with a tiny government that has such great results?
This is the bina