T cell cross-reactivity and the Herd immunity threshold

By Nic Lewis

An interesting new paper by Marc Lipsitch and co-authors, “Cross-reactive memory T cells and herd immunity to SARS-CoV-2”, has recently been published.[1] It discusses immunological and epidemiological aspects and implications of pre-existing cross-reactive adaptive immune system memory arising from previous exposure to circulating common cold coronaviruses. They argue that key potential impacts of cross- reactive T cell memory are already incorporated into epidemiological models based on data of transmission dynamics, particularly with regard to their implications for herd immunity. I believe that they are mistaken on the herd immunity point, as I will show in this article.

The first point to make is that cross-reactive T cells were never thought to be the main cause of the herd immunity threshold (HIT)[2] being lower for COVID-19 than the oft-quoted {1 – 1/R0} level, which generally applies for vaccination. Heterogeneity in social connectivity (contact rates) is typically estimated to lower the HIT much more than heterogeneity in biological susceptibility to the causative SARS-CoV-2 virus.[3]

Possible effects of cross-reactive T cells on infection progression

Lipsitch and co-authors note that recent reports have shown that SARS- CoV-2 cross-reactive memory T cells, very largely CD4+ T-cells arising from previous exposure to circulating common cold coronaviruses, are detectable in ~28–50% of individuals not exposed to SARS- CoV-2. They say that only tissue-resident memory T cells (TRM cells) can mount a fast response, with recirculating TCM and TEM T cells taking several days to start fighting an infection. They point out that CD4+ T-cells generally limit disease severity, reduce the viral burden and/or limit the duration of the disease rather than preventing an initial infection.

While I do not intend to challenge any of the foregoing points here, it should be noted that they treat an ‘infection’ as including a case where so few cells have been infected that any (RT-)PCR test for the virus would be negative.

The paper states that CD4+ T cell-mediated memory responses to a virus may involve some or all of CD4+ TFH cell types (required for B cell help and thus almost all neutralizing antibody responses), TH1 and CTL cell types (with direct antiviral activities in infected tissues), and that the CD4+ T cells involved may be TRM cells, or slower to respond recirculating TCM/TEM cells.

The authors go on to propose four immunological scenarios for the impact of cross-reactive CD4+ memory T cells on COVID-19 severity and viral transmission. The four model scenarios they put forward are:

  1. Reduction of lung burden: CD4+ T cells reduce COVID-19 symptoms and lung viral load but have minimal impact on upper respiratory tract (URT) viral load.
  2. TFH cell-accelerated antibodies: CD4+ TFH cells trigger a faster and better antibody response, resulting in accelerated control of virus in the URT and lungs.
  3. TRM cells in the URT: CD4+ TRM cells at the site of infection enable rapid control of virus in the URT and lungs.
  4. Transient infection: TRM cell immunity ‘blitzes’ viral replication in the URT leading to the elimination of all infected cells within a day of the initial infection, at the portal of entry.

The first three scenarios, along with the case where no cross-reactive T cells exist, are represented in Fig.1 of the paper, reproduced below.

Which models do the data fit?

The authors argue that biological evidence implies model scenario 4 is very unlikely where only CD4+ T cells are involved. They point out that if pre-existing CD4+ TRM cell immunity was so extreme as to preclude significant viral replication, seroconversion (that is, a de novo antibody response to SARS- CoV-2) would not occur. Such individuals would not be detectable by virological (e.g., PCR) or serological diagnostic tests and would not shed virus; effectively, these individuals would be immune to infection and not reported as cases. The authors say that evidence for other human coronaviruses makes this implausible, and that when epidemiological evidence of very high attack rates in some ship-based outbreaks is added scenario 4 is highly unlikely.

However, in the most studied ship-based outbreak the proportion infected was under 20%.[4] Moreover, the results of a study that Lipsitch et al. do not cite[5] show that, in households where one person was confirmed as having COVID-19, a substantial proportion of other household members had negative PCR test results, implying that they were not infective, despite most of them having typical COVID-19 symptoms. Moreover, these individuals did not develop detectable SARS-CoV-2 specific antibodies, but did develop SARS-CoV-2 specific (as opposed to cross reactive) T cell responses, implying that they had been infected to some degree by SARS-CoV-2 .

Notwithstanding that the sample size was small in that study, it appears to cast some doubt on Lipsitch et al.’s assertion that scenario 4 is highly implausible. It also casts doubt on their subsequent assertion that almost all people infected by SARS-CoV-2 seroconvert (develop antibodies against it), although the test used might have been insufficiently sensitive to detect low antibody levels. In that connection, Lipsitch et al. say that a recent study[6] observed [only] about 3 cases of non-PCR confirmed potentially asymptomatic COVID-19 cases with T cell responses in the absence of seroconversion, but their interpretation of that study’s results has been challenged.[7]

A substantial proportion of PCR-test positive individuals – in some localised outbreaks, the vast majority of them – have asymptomatic infections. In the most studied ship-based outbreak4 almost half of infected individuals remained asymptomatic throughout.[8] If that is due to T-cell cross reactivity, acting in combination with innate immune responses, then only model scenarios 3 or 4 would fit, since model scenarios 1 and 2 imply significant symptoms.

In the remainder of this article I will not pursue the possibility of model scenario 4 being relevant. Rather, I will focus on showing that the implications for herd immunity of model scenario 3 (possibly involving also model scenario 2), as varied to take account of variation in viral dose and innate immune system strength, are very likely not already taken into account in simple epidemiological models based on transmission dynamics data. In this connection, it should be noted that the extent and quality of the available data, both biological and epidemiological, does not provide high quality evidence, so drawing firm conclusions either way is difficult.

The low level of asymptomatic transmission

Importantly, there is quite strong evidence that infected individuals transmit SARS-CoV-2 much more weakly if they are asymptomatic (and not just presymptomatic). Biological evidence neither proves nor disproves that a positive PCR test for SARS-CoV-2 implies significant infectivity (although a negative PCR test can be taken as implying a lack of significant infectivity).[9] However, epidemiological evidence strongly suggests that transmission by asymptomatic individuals is far lower than that by symptomatic or presymptomatic individuals.

A number of studies have investigated transmission from index cases who remained asymptomatic throughout their infections. A review study[10] estimated that the mean household secondary attack rate from asymptomatic cases was only 3.5% of that from symptomatic cases. As that study noted, household secondary attack rate provides a useful estimate of both the susceptibility of contacts and infectiousness of index cases. However, both in that study, and in another review study[11] that estimated a much higher ratio than 3.5%, the statistical analysis appears to be seriously flawed.[12] It is therefore necessary to consider the actual results of the relevant original studies that they reviewed. Two of those studies[13] [14] found no instances of asymptomatic transmission, although the number of contacts concerned was very small in one case. Two other studies each found one case of asymptomatic transmission, out of respectively 305 and 119 contacts,[15] [16] with corresponding relative risks of 6% and 19%. Averaging the risk ratios of all four studies, in a way that gives appropriate weight to the evidence each provides, gives an overall transmission risk ratio estimate of 8% for asymptomatic cases, relative to symptomatic and presymptomatic cases.[17]

That is, an asymptomatic infected person, as in Lipsitch et al. model scenario 3, appears to be only one-tenth or less as likely to transmit the virus as does a symptomatic or presymptomatic person. This conclusion does not have to depend on asymptomatic infectees having a much lower viral load in their URT, which may not be the case. They could for instance transmit less because of an absence of coughing (particularly that involving expectoration15), less deep breathing or a similar factor; because more of their PCR-measured viral load does not represent viable viruses; and/or because their viral load remains at an infective level for a shorter period.

The likely importance of viral dose (inoculum) and innate immune responses

Two factors that Lipsitch et al. do not include in their model scenarios, but which seem likely to be very relevant, are the magnitude of the viral dose and the strength of a person’s fast responding innate immune system. Both the symptoms, as to their likelihood and severity, and the infectivity of an individual exposed to SARS-CoV-2 are expected to depend on the viral dose that their exposure involves[18] [19] and on the strength of their innate immune system, as well as on any cross-reactive T cell and/or antibody adaptive immune system memory. I will concentrate here on differences arising from the interaction between viral dose and cross-reactive T cells, but in reality differences in innate immune system strength, and in general health and other factors, will likewise affect how somebody reacts to viral doses of varying strength and to what extent they become ill and/or infective.

Box 1: Might low viral dose explain Tokyo’s COVID-19 epidemic?Evidence from a study[20] of 1877 asymptomatic (at time of testing) company employees from 11 disparate locations in Tokyo is consistent with the importance of viral dose. The study showed seroprevalence increasing from 6% to 47% between late May and late August. If the sample is representative of the Tokyo metropolitan area, which the authors suggest it may be, that implies seroconversion of about 5.7 million individuals during the study period.
Since the corresponding number of deaths attributed to COVID-19 appears to have been little more than 30, that implies an infection fatality rate in Tokyo that might be as low as 0.0006% – around a thousand times lower than generally estimated. In Japan, the very high rate of mask wearing (and generally high personal hygiene standards) may have reduced viral doses sufficiently for the vast majority of infections to be asymptomatic, and for almost all symptomatic cases to be mild, irrespective of the presence of cross-reactive T cells.[21] [22]

It seems entirely possible that where the viral dose is sufficiently low, a person with cross reactive CD4+ T cells might either be infected so little that – whether or not a PCR test would be positive, at a sufficiently large cycle threshold (high sensitivity) – they not only remain asymptomatic but also have negligible infectivity. In effect, given a sufficiently low viral dose, Lipsitch et al.’s model scenario 3 might produce rather similar effects to what their model scenario 4 would do for a high viral dose. It appears, for most purposes, to be inappropriate to regard such a non-infective, healthy person as a COVID-19 case or even as being infected at all.[23] Such persons are accordingly treated here as not having been infected. However, it appears possible that a low viral load might, without resulting in symptoms or non-negligible infectivity, nevertheless induce effective immunity through the development of SARS-CoV-2 specific antibodies and/or T cells.

By contrast, Lipsitch et al. appear to regard someone as having been infected even if only a single cell in their body has been invaded by a virus. While this definition may be logical from a technical biological angle, it does not seem appropriate from an epidemiological viewpoint. For epidemiological purposes, what is relevant is whether and to what extent a person is or will become ill, infective and/or immune.

Where the viral dose is fairly high, even if a person has cross reactive CD4+ T cells, they would almost certainly test PCR positive, and be more likely to develop symptoms. Model scenarios 2 and 3 in the paper may both be relevant in these cases. While in such a case the person concerned would be infective, albeit much less so if asymptomatic, if they had cross reactive CD4+ T cells they would probably be considerably less infective (and be much more likely to be asymptomatic or to have mild symptoms).

Insofar as infected individuals are asymptomatic and of low (but non-negligible) infectivity, it may be that in cases where they do transmit infection the viral dose is usually sufficiently low for the person thereby infected also to be asymptomatic and of low infectivity, in which case such asymptomatic transmission will contribute to the gradual spread of immunity while not leading to disease.[24]

Modelling the effects of varying susceptibility and infectivity arising from cross-reactive T cells

I have built a greatly simplified toy model that illustrates the possible implications for epidemic progression and herd immunity of cross-reactive T cells that have the effects discussed in this article. The model stratifies the population into two equal parts, one possessing cross-reactive T cells and the other not. It distinguishes symptomatic and asymptomatic infections, the latter having only one-ninth as high a probability of causing infection as the former.

The detailed assumptions made in the model are set out in an Appendix. While these assumptions are purely illustrative, they are intended to be broadly consistent with existing evidence and the foregoing discussion in this article. The key assumptions regarding the effects of cross-reactive T cells are that their presence halves the risk of infection from a potentially infective contact, quarters the probability of any infection being symptomatic, and may result in immunity developing in a substantial proportion of those cases where infection does not occur.

The modelled epidemic is seeded by the symptomatic infection of one naïve individual (a person without cross-reactive T cells). The number of close contacts per generation is then adjusted to produce, after the epidemic has adjusted from the initial seeding pattern to its natural pattern, a reproduction number early in the epidemic – which will therefore closely approximate R0 – of 2.4.

The toy model’s projections show that, after initial exponential growth, new infections start to decline, indicating that herd immunity has been achieved. At that point, 41% of the population has been infected, with approximately 43% of infections being asymptomatic. At 41%, the HIT is slightly over two-thirds of the classical HIT level for a homogeneous population, being 58%.[25]

A further 20% of the population will have become immune without, for all practical purposes, having had an infection. If on the other hand no exposed but uninfected (i.e., asymptomatic and non-infective) individuals develop immunity, then the HIT is closer to the classical level, but still lies more than 10% below it. If the probability of being infected is reduced by 85% in the presence of cross-reactive T cell memory, the HIT could be one-third below the classical HIT even if no exposed but uninfected person develops immunity. It is not suggested that such a large differential is  likely. However, it does prove that cross-reactive T cell memory, in combination with varying viral dose (and innate immune system strength) can result in a substantially lower herd immunity threshold than that estimated from data earlier in the epidemic using homogeneous population compartmental SIR/SEIR models, as is routinely done.

A more realistic model would incorporate continuous probability distributions for all the key parameters. But the basic point illustrated by the very simple model would remain valid. Homogeneous population based compartmental models imply that epidemic growth will slow pro rata to the shrinking pool of uninfected people. But where there is variation within the population as to how susceptible people are to infection, so that more susceptible individuals are on average infected earlier, the epidemic growth is bound to reduce more rapidly than that. As a result, the herd immunity threshold will be lower than if the population were homogeneous, with the reduction of the HIT being greater if less biologically susceptible individuals also have, if infected, lower biological infectivity.

Conclusion

I have demonstrated that the claim by Lipsitch et al. that the potential impacts on the herd immunity threshold of cross- reactive T cell memory are already incorporated into epidemiological models based on data of transmission dynamics is mistaken, even assuming that they are correct in arguing that their model scenario 4 is highly implausible.

In this article I have only considered the possible effects of cross-reactive T cells. However, even when combined with other causes of interpersonal variation in biological susceptibility, including age, such heterogeneity is not thought to be the main reason why the herd immunity threshold will be lower than the classical level for a homogeneous population. In practice, interpersonal variation in contact rates (social connectivity) is usually thought to be a much more important reason. 3

Appendix – Assumptions made in the toy model of the effects of cross-reactive T cells

  1. The population is one million and is homogeneous except that only 50% of people have cross-reactive memory T-cells.
  2. The generation interval is fixed, infected individuals are only infectious in the generation interval after they become infected and are uninfectious and immune thereafter.
  3. Infections are by close contact only. The number of close contacts by an infected person is independent of their T cell status and whether or not their infection is asymptomatic (never symptomatic), and each person who becomes infected has only had one contact with an infectious person during the generation interval in which they become infected.
  4. A close contact between a symptomatic (including presymptomatic) infectee and a naïve individual (one without cross-reactive T cells) results in infection 90% of the time, with 80% of such infections being symptomatic, due to a high average viral dose being involved.
  5. A close contact between an asymptomatic infectee and a naïve individual results in infection 10% of the time, with 20% of such infections being symptomatic, the viral dose being lower.
  6. A close contact between a symptomatic infectee and a resistant individual (one with cross-reactive T cells) results in infection 45% of the time, with 20% of such infections being symptomatic.
  7. A close contact between an asymptomatic infectee and a resistant individual results in infection 5% of the time, with 5% of such infections being symptomatic.
  8. Where such a low viral dose is transmitted on a close contact that a resistant recipient not only has no symptoms but is completely non-infective, they are treated as not being infected but (except if stated otherwise) in 60% of such cases they nevertheless become immune.

Nicholas Lewis                          14 October 2020


[1]  Marc Lipsitch, Yonatan H. Grad, Alessandro Sette and Shane Crotty: Cross-reactive memory T cells and herd immunity to SARS-CoV-2. Nature Reviews Immunology 6 October 2020 https://doi.org/10.1038/s41577-020-00460-4

[2]  The herd immunity threshold is the proportion of the population that have become infected at the point where each new infection causes, on average, no more than one further infection. For an epidemic in a homogeneous population, it will be {1 – 1/R0}, where R0 is the basic (initial) reproduction number.

[3]  e.g., 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

[4]  The Diamond Princess. 712 out of 3,711 on board tested PCR-positive, with at least 295 and probably closer to 334 cases (295 from Tokyo plus 40 returned on charter flights, one of whom died from COVID-19) remaining asymptomatic throughout their infection. https://www.mhlw.go.jp/stf/newpage_11441.html

[5]  Gallais, F., Velay, A., Wendling, M.J., Nazon, C., Partisani, M., Sibilia, J., Candon, S. and Fafi-Kremer, S., 2020. Intrafamilial exposure to SARS-CoV-2 induces cellular immune response without seroconversion. MedRxiv. https://www.medrxiv.org/content/medrxiv/early/2020/06/22/2020.06.21.20132449.full.pdf

[6]  Sekine, T. et al. Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. Cell https://doi.org/10.1016/j.cell.2020.08.017 (2020).

[7]  https://twitter.com/WesPegden/status/1313649435642077184

[8]  That is consistent with the findings of Sakurai et al., Natural History of Asymptomatic SARS-CoV-2 Infection. New England Journal of Medicine. 2020 Jun 12 https://www.nejm.org/doi/full/10.1056/NEJMc2013020

[9]  https://www.cebm.net/covid-19/infectious-positive-pcr-test-result-covid-19/

[10] Madewell, Z.J., Yang, Y., Longini Jr, I.M., Halloran, M.E. and Dean, N.E., 2020. Household transmission of SARS-CoV-2: a systematic review and meta-analysis of secondary attack rate. medRxiv. [1 August version]

[11] Buitrago-Garcia D, et al. (2020) Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and metaanalysis. PLoS Med 17(9): e1003346. https://doi.org/10.1371/journal.pmed.1003346

[12] Madewell et al. included a study where the secondary attack case rather than the index case was asymptomatic. Buitrago-Garcia D, et al., who estimated a relative risk of 0.35 for asymptomatic transmission,  included in that estimate a study of presymptomatic transmission (their reference 111) and an estimate based on combined asymptomatic and presymptomatic transmission (from their reference 65), and they wrongly estimated very high asymptomatic transmission risk from studies that found zero cases of it.

[13] Cheng HY, Jian SW, Liu DP, Ng TC, Huang WT, Lin HH, et al. Contact Tracing Assessment of Covid-19 Transmission Dynamics in Taiwan and Risk at Different Exposure Periods before and after Symptom Onset. JAMA Intern Med. 2020. Epub 2020/05/02. https://doi.org/10.1001/jamainternmed.2020.

[14] Park SY, Kim YM, Yi S, Lee S, Na BJ, Kim CB, et al. Coronavirus Disease Outbreak in Call Center,

South Korea. Emerg Infect Dis. 2020. https://doi.org/10.3201/eid2608.201274

[15] Luo L, Liu D, Liao X-l, Wu X-b, Jing Q-l, Zheng J-z, et al. Modes of Contact and Risk of Transmission in Covid-19 among Close Contacts. bioRxiv. 2020 [March 26 version] https://www.medrxiv.org/content/10.1101/2020.03.24.20042606v1

[16] Zhang W, Cheng W, Luo L, Ma Y, Xu C, Qin P, et al. Secondary Transmission of Coronavirus Disease from Presymptomatic Persons, China. Emerg Infect Dis. 2020. https://doi.org/10.3201/eid2608.201142

[17] Averaging over the four studies, weighting by the number of contacts by asymptomatic index cases, gives a pooled relative risk estimate of 8.2%. A more sophisticated meta-analysis using the R software Fixed effects (Mantel-Haenszel) function in the rmeta package estimates a pooled study relative risk of 7.9%, with a 75% probability that it does not exceed 13% and a 90% probability that it does not exceed 20% (assuming that the confidence intervals are symmetrical).

[18] Steinmeyer, Shelby H., Claus O. Wilke, and Kim M. Pepin. “Methods of modelling viral disease dynamics across the within-and between-host scales: the impact of virus dose on host population immunity.” Philosophical Transactions of the Royal Society B: Biological Sciences 365.1548 (2010): 1931-1941.

[19] Goyal, Ashish, et al. “Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events.” medRxiv (2020) [7 August version].

[20] Hibino, Sawako, et al. “Dynamic Change of COVID-19 Seroprevalence among Asymptomatic Population in Tokyo during the Second Wave.” medRxiv (2020). [23 September version]

[21] Gandhi, Monica, Chris Beyrer, and Eric Goosby. “Masks do more than protect others during COVID-19: Reducing the inoculum of SARS-CoV-2 to protect the wearer.” Journal of general internal medicine (2020): 1-4.

[22] Gandhi, Monica, and George W. Rutherford. “Facial Masking for Covid-19—Potential for “Variolation” as We Await a Vaccine.” New England Journal of Medicine (2020).

[23] While such cases might give a positive result on a PCR test at some point, such a test result might represent  detection only of non-viable virus fragments, or a viable viral load that is too low to be infective.

[24] Unfortunately there are too few recorded cases of asymptomatic transmission to provide reliable evidence on this point, but what evidence does appear to exist is consistent with this argument. Zhang et al. identified one case of asymptomatic transmission, which resulted in an asymptomatic infection, while 73% of the eleven cases of symptomatic or presymptomatic transmission they identified resulted in a symptomatic infection. (Luo et al. unfortunately did not indicate the symptom status of the asymptomatic transmission case that they identified.)

[25] For an R0 of 2.4, the classical herd immunity threshold is {1 – 1/2.4} = 0.583

420 responses to “T cell cross-reactivity and the Herd immunity threshold

  1. Matthew R Marler

    thank you for the essay.

    In this connection, it should be noted that the extent and quality of the available data, both biological and epidemiological, does not provide high quality evidence, so drawing firm conclusions either way is difficult.

    It’s a classical ill-posed inverse problem. Many combinations of the rates/intensities of the microprocesses are compatible with particular parameter values in the epidemiological model. All of the processes contribute to the observed process, in different amounts in different people.

    Still worth study — no denying that — and this is a good essay.

  2. It’s been discussed that those who in the past have been exposed to an innumerable number of coronaviruses over a lifetime may in fact have a protective immunological responses to CoV19.

    • Robert Starkey

      There may be individuals who have immunity to covid 19. If the percentage of the total population is low does it matter? (From a public policy perspective)

      Will any region ultimately be spared?

      • …no more than you can spare a region from the The consequences of common cold.

      • Depends on the definition of consequences.
        We know from the past that populations with no exposure to flu, can die from it in great numbers (North & Central American, Caribbean indigenous). Thus it seems very possible that partial immunity means merely having the sniffles and feeling bad as opposed to dying.
        Secondly, I haven’t seen this examined but there seems to be universally better outcomes in Asia vs. COVID-19 than in Europe or the Americas. This is not purely a government-based outcome because there are poor as well as shambolic governments there.
        India is probably the worst performing in Asia – and their COVID-19 mortality rates are 1/10th that of the Western democracies. This is no longer a minor difference.
        Whether this is environmental (pre-existing coronavirus exposure), societal (BCG vaccination) – something is very different.
        It isn’t age – Japan is really old and has done fine even as India is relatively young.
        It isn’t government response: some governments have imposed total lockdown. Others have no lockdown. And still others have switched between lockdown and no lockdown.

      • Wolf

        Notwithstanding Japan I do think age is a big factor. Many of the least affected countries have a very young population with a low obesity factor.

        As for Japan, social distancing and hand washing have been an integral part of their social customers for Years

        Tonyb

      • And, hydroxychloroquine cuts through all of that…

      • @Tonyb
        Age is a factor – but India is really young (27.6 years) and is the worst performing in Asia.
        Asia isn’t that young, overall though
        South Korea: 41.2
        Japan: 46.9
        Taiwan: 39.7
        China: 37.1
        Thailand: 37.2
        Vietnam: 30.1
        US: 37.9
        UK: 40
        France: 41.2
        Spain: 42.3
        Note that the US is younger than South Korea and Taiwan and isn’t much older than China.
        Secondly, even with low average age – the mortality rates for COVID-19 are very small: death rates per million are low 4 digits per million population even in the worst hit countries/cities/regions. Or in other words – even countries with low average ages have old people. I’ve looked closer at some of the actual demographic profiles – and the difference in the 60+ groups isn’t 10x between almost any of the 2 nations above.
        So again, it seems likely there is some other factor than lockdown and/or mask wearing.

  3. Nic, In several places you say Model 4. Figure 1 from the paper has a No cross reactive panel and 3 Models. When you say Model 4 do you mean Model 3? Or is there a 4th model as well?

    • Model scenario 4 is Transient infection – the one numbered 4 in my list. It is not included in Figure 1, as Lipsitch et al. considered it to be ‘highly implausible’. The headings of each panel in Fig. 1 state which model scenario is involved; none of them relates to model 4.

  4. Re: ” In that connection, Lipsitch et al. say that a recent study[6] observed [only] about 3 cases of non-PCR confirmed potentially asymptomatic COVID-19 cases with T cell responses in the absence of seroconversion, but their interpretation of that study’s results has been challenged.[7]”

    Challenged by Wes, who has no expertise nor competence in this topic, unlike the authors of the study he’s responding to; I know since I’ve dealt with Wes multiple times, and actually read the study he cited. Wes not even familiar with the literature. If he were, then he’d know the sensitivity for the assay used in that study is low, and thus one would expect it to yield a higher proportion of false seronegatives. That effect would be relatively larger, since the expected proportion of true seronegatives is low. This has been explained over and over and…

    Click to access 2020.08.05.20169128v1.full.pdf

    Click to access Evaluation_of_Diasorin_Liaison_anti_SARS_CoV_2.pdf

    Re: “If the sample is representative of the Tokyo metropolitan area, which the authors suggest it may be, that implies seroconversion of about 5.7 million individuals during the study period.
    Since the corresponding number of deaths attributed to COVID-19 appears to have been little more than 30, that implies an infection fatality rate in Tokyo that might be as low as 0.0006% – around a thousand times lower than generally estimated.”

    Give me a break. This was addressed weeks ago, covering how the sampling methodology for that paper in non-representative. It basically amounts to local workplace outbreaks from a non-randomized sample of volunteers, not representative of infections across the general population of Tokyo. This is at least the 4th time you’ve under-estimated the fatality rate of SARS-CoV-2, and at least the 2nd time you’ve done it using non-representative samples that over-estimate seroprevalence:

    Re: “While these assumptions are purely illustrative, they are intended to be broadly consistent with existing evidence and the foregoing discussion in this article. The key assumptions regarding the effects of cross-reactive T cells are that their presence halves the risk of infection from a potentially infective contact, quarters the probability of any infection being symptomatic, and may result in immunity developing in a substantial proportion of those cases where infection does not occur.”

    You’re again making the mistake of assuming cross-reactive T cells are significantly beneficial, since you think that helps you reach your politically-motivated conclusion that SARS-CoV-2 is less dangerous and thus you can avoid policies you dislike, like lockdowns. You’ve done this for months, besides being repeatedly corrected by those who know more on this topic than you.

    There’s every reason to think that immune cells may need to have not seen a virus before SARS-CoV-2 (i.e. be naïve) in order to be effective, such that it may be detrimental if they are cross-reactive and bind to another seasonal coronavirus before seeing SARS-CoV-2:

    “Antigen-specific adaptive immunity to SARS-CoV-2 in acute COVID-19 and associations with age and disease severity”
    Not yet peer-reviewed: “Pre-existing T cell memory as a risk factor for severe 1 COVID-19 in the elderly”

    There’s every reason to think that the TCR repertoire needs to shift to address SARS-CoV-2, where exposure to seasonal coronaviruses is insufficient for causing that shift, while exposure to SARS-CoV-2 eventually is:

    “Viral epitope profiling of COVID-19 patients reveals cross-reactivity and correlates of severity”
    Not yet peer-reviewed: “SARS-CoV-2 T-cell epitopes define heterologous and COVID-19-induced T-cell recognition”

    There’s every reason to think SARS-CoV-2 exploits the T cell response to cause illness, resulting in a hyper-inflammatory cytokine storm and T cell exhaustion that harms the patient, such that cross-reactive T cells would be useless and/or detrimental:

    “Robust T cell response towards spike, membrane, and nucleocapsid SARS-CoV-2 proteins is not associated with recovery in critical COVID-19 patients”
    “Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients”
    “Systematic examination of T cell responses to SARS-CoV-2 versus influenza virus reveals distinct inflammatory profile”
    “Immunologic features in Coronavirus Disease 2019: Functional exhaustion of T cells and cytokine storm”

    And if cross-reactive humoral immunity (which is better designed to prevent infection and disease that is the T cell response, since the BCR and antibodies can recognize viral antigens without help, while the TCR needs MHC help) fails to prevent disease, then there’s every reason to think a cross-reactive T cell response would fail as well:

    Not yet peer-reviewed: “Pre-COVID-19 humoral immunity to common coronaviruses does not confer cross-protection against SARS-CoV-2”
    Not yet peer-reviewed: “Prior infection by seasonal coronaviruses does not prevent SARS-CoV-2 infection and associated Multisystem Inflammatory Syndrome in children”
    Not yet peer-reviewed: “Seroprevalence and correlates of SARS-CoV-2 neutralizing antibodies: Results from a population-based study in Bonn, Germany”

    So no, Lewis, the assumptions of your model are not “broadly consistent with existing evidence”. They are, at best, non-expert wishful thinking. This is not your field, and it shows. Your ideologically-motivated, epistemic trespassing is not helpful nor or informative to anyone with expertise in this topic, including the authors of the research you’re criticizing. Enough already.

    “Cross-reactive T cell memory may or may not affect COVID-19 disease severity in individuals.”
    https://www.nature.com/articles/s41577-020-00460-4

  5. The body has a number of different immune mechanisms.
    Of which Cross-reactive memory T cells activation is one.
    The concept that Cross-reactive memory T Cell activation on its own can be responsible for stopping a new viral infection on its own and without the need for development of B -cell antibodies is not new.
    Nic is not the first to go down what I think is a rabbit hole of logical reasoning.

    • Viral infections have a logical and consistent method of being dealt with by the body.
      The virus has a method of getting to its target cells.They often go through a number of different cell replications to reach the ultimate destinations.
      This is in the case of C19 and most other colds and viruses through both the respiratory tract and the blood circulation.
      Source viral load on surface to hand to mouth, nose or eye.
      Source viral load in air to mouth,nose, eye or airways.
      Source blood transfusion or bite, direct to blood stream.* rare.

      Step 1 – attachment to a cell in the eye, nasal passages, mouth or respiratory tract. Here the virus first enters a susceptible cell or cells depending on the load. Note not many T-cells available to block this step externally.
      Step 2 reproduction giving billions of virus particles released by either viral mediated cell lysis. [Did not need those T cells at all to kill a cell] or programmed continual extrusion of complete viral particles through the cell into the bloodstream. External release leads to infection of neighboring cells by local spread..
      Step 3 blood stream spread back to preferred sites in the nasal passages and airways. Because these are the sites from which it can spread to the next target. Incidental infection of non target cells liver spleen, anything really but not very interested as not useful.
      Step 4 blood stream spread to Immune system cells B and T system work in conjunction. The Immune cells have to be easily targeted because otherwise they cannot detect and overcome the viruses in the first place.
      This would pose a problem for an activated memory T cell that became infected.

      • The combined workings of the Immune system lead to the production of multiple antibodies to the virus shell components [including the spike]
        The Immune B cells multiply rapidly adding to the amount of antibody level.
        Cross-reactive memory T cells, very largely CD4+ T-cells, Follicular helper T (Tfh) cells are specialized providers of T cell help to B cells, and are essential for germinal center formation, affinity maturation, and the development of most high affinity antibodies and memory B cells.
        In other words they develop specifically with and in order to help produce more antibodies of the specific type needed.
        I see by the graphs of the study that this is in less than 48 hours.
        * A very salient point for previous infections.
        Any virus that gets to the stage of being blood borne and reaching target cells also always reaches the immune system cells and stimulates an antibody response.
        If the Immune system is normal, it includes working B cells that produce antibodies.
        Fact 1 in the normal person with a proven viral infection and response there will always be a detectable Antibody response within 2 days.

        Corollary, a normal person without an antibody response to a particular virus did not and cannot have had a viral infection with that virus.

      • Conclusions.
        “in households where one person was confirmed as having COVID-19, a substantial proportion of other household members had negative PCR test results, implying that they were not infective, despite most of them having typical COVID-19 symptoms.”
        Typical Covid-19 symptoms do not imply covid-19 in any way shape or form.
        Every mild covid infection is indistinguishable from a common cold.
        What is more likely? A group of people in a hose caught a viral cold and one then contacted symptonatic covid?
        or a bunch of people caught covid and only one got sick?
        Who coincidentally was always the only one with covid antibodies?
        Amazing.
        My cat has stripes, it must be either a juventus supporter, a zebra or a tiger.
        Same symptoms, typical really. Common sense would dictate that it is a cat [a cold[ with the other possibilities increasingly unlikely.

      • Final comment re rapid response. While it takes 48 hours to produce detectable new antibodies if there is cross reactivity with a previous corona virus there will be rapid induction of antibodies to that common antigen within hours , If it works, which it should it would lead to very little or no symptoms and quick resolution with no Covid specific antibody [recognised only as a cold antibody to a common compnent even though it worked.
        There would also be an activation of TRM cells to hasten susceptible cell death.
        and so called CD8 rsponse.
        T cell CD8 reactive populations would be virtually indistinguishable from a T cell CD8 activated for covid only cell response.
        No easy way of telling them a apart .
        If the cells are incapable of producing antibody to the virus then the T cells can have all the cross reactive memory they want and cannot affect a thing because if a B cell antibody response to covid or corona is not produceable then the T cells will also not be able to react to that virus.
        If the person has had a common cold at any stage in the preceding 3 months then of course there will be activated T cells with a meaningless Sars profile still persisting from that cold response but no way of reacting to covid or a covid related corona virus until they develop the specific antibodies to that virus
        How many covid cases have had a cold in the preceding 3 months?
        Why is this so hard to get through, other than the buckets of research cash available for dodgy ideas?

      • “Typical Covid-19 symptoms do not imply covid-19 in any way shape or form.”
        I didn’t say that they did.

        “Same symptoms, typical really. Common sense would dictate that it is a cat [a cold”
        So how come these individuals developed SARS-CoV-2 specific (as opposed to cross reactive) T cell responses, as I wrote in the next sentence?

        “Fact 1 in the normal person with a proven viral infection and response there will always be a detectable Antibody response within 2 days.”
        That is fantasy, not fact. Serological antibody tests typically have a low detection rate until more than a week after infection.

      • niclewis |
        “Fact 1 in the normal person with a proven viral infection and response there will always be a detectable Antibody response within 2 days.”

        That is fantasy, not fact. Serological antibody tests typically have a low detection rate until more than a week after infection.

        I could quibble. I hate losing an argument.
        You are referring to seroconversion which by definition is when antibody levels are detected in the bloodstream.
        In which and every case you are right.

        Virology science says that IgM is produced very early on in the disease and is not initially released actually going onto the membrane of the B cells. presumably detected by both EM and PCR techniques in the laboratory.

        An article
        “Chronological evolution of IgM, IgA, IgG and neutralisation antibodies after infection with SARS‐associated coronavirus”
        states
        “the present study showed clearly that IgG seroconversion can start as early as 4 days after the onset of illness.”

        Quibbles aside you are still right.

      • niclewis | October 15, 2020 at 5:09 am |
        “Typical Covid-19 symptoms do not imply covid-19 in any way shape or form.” I didn’t say that they did.

        Somebody did
        “Moreover, the results of a study that Lipsitch et al. do not cite[5] show that, in households where one person was confirmed as having COVID-19, a substantial proportion of other household members had negative PCR test results, implying that they were not infective, despite most of them having typical COVID-19 symptoms.”

        In fact, as you wrote in the next sentence
        “Moreover, these individuals …. did develop SARS-CoV-2 specific (as opposed to cross reactive) T cell responses, implying that they had been infected to some degree by SARS-CoV-2 .”

        I interpret, maybe wrongly, that here you do imply that people with covid-19 like symptoms do [implied] have an infection with Covid 19 when clearly there is no antibody proof of this, only guilt by association.

        “So how come these individuals developed SARS-CoV-2 specific (as opposed to cross reactive) T cell responses, as I wrote in the next sentence?

        SARS-CoV-2 specific T cell responses are not opposed to cross reactive responses, They are both similar reactive responses and unfortunately not at all that specific.
        You have a corona virus or other cold virus infection which causes a T cell
        reactive response.
        Multiple changes in multiple parameters definitely showing a recent infection.
        Cross reactive?
        There are thousands of different individual T cell activations to different protein sub segments.
        Sigh.
        Some of these will correspond to protein sub segments from covid 19,SARS, rubella, influenza virus, or, as my wife says, whatever.
        Inevitable.
        Activated T cell profiles are matched to the disease being tested for.
        “This is a Rubella specific response,this Covid 19, this SARS.
        What they should not say is not that an activated T cell response is specific for a viral disease, it is only associated with a viral disease in a particular laboratory.
        and we have no way of proving that this response must be a specific virus.

        I will put it this way, How many real people have been exposed to SARS and lived to tell the tale?
        Not many.
        How many real people are you now claiming to have preexisting exposure to a SARS like virus to develop this SARS like response when exposed to a common cold. Remember none of them have antibodies to Covid 19?
        So out of a handful of people with prior exposure to a lethal infection how do they keep turning up in all these studies?
        The obvious answer is that they do not.
        People are confusing normal activated or cross activated T cell profiles with SARS profiles because the profiles are not specific.

  6. Atomski’s missives are at best unreadable and at worst incomprehensible. He uses a scattergun approach of tweets, whole articles and a enclave of references that may or may not be relevant to an argument he is incapable of articulating. This is conflated with a purely adversarial stance and expressed with an arrogant assurance at odds with the complexity and uncertainty of the topic.

    • Robert I Ellison: Atomski’s missives are at best unreadable and at worst incomprehensible.

      Atomsk Sanakan’s post are usually worth reading in their entirety and usually refer to sources that deserve serious consideration.

      If you can’t understand them, well that’s on you.

      • Tweets, lists of irrelevant articles unhinged from coherent and succinct argument, dogmatically adversarial and with a fixed and rigid worldview. I’ve wasted enough time on the perennially oblivious.

      • Robert I Ellison: I’ve wasted enough time on the perennially oblivious.

        So write coherently about specific propositions. Avoid any perennially oblivious.

      • After decades of technical and creative writing – I think I can organise a coherent argument. Although I no longer have the patience to write for an audience. I write for fun in the way I want to on ideas that are only graspable if you are there or almost so anyway.

        Somewhere recently I have written that the creative and fun bit of science is to synthesise disparate empirical facts into a coherent worldview.

        I don’t get that sense of creative energy and excitement, wonder and awe, from either of you. More like pompous and self important pronouncements. Oh how Feynman warned us against you.

      • > dogmatically adversarial and with a fixed and rigid worldview.

        Unmatched in mastery of unintentional irony.

      • I did have a reply that used the logical fallacy of the loaded question ironically.

        Somehow ‘when did you stop flogging a dead horse’ crossed a line.

  7. Nik

    I pass no comment on the scientific correctness of the information in this link( scroll to foot to see the article)

    https://www.dailymail.co.uk/news/article-8839007/Almost-half-Britons-likely-catch-Covid-19-Type-O-blood.html

    It says that people with one blood type are much less susceptible to covid than other blood types

    Tonyb

    • I think the same from noted or suspected from studies of some of earliest cases in China.

    • Tonyb
      The findings reported look to me to agree with other results published a little while ago – unless they are referrring to a study that came out quite a while ago.

      • So, it seems your chances of being infected or of being seriously Ill from covid could be dependent on your blood group, your level of vitamin d, your level of obesity, your level of fitness, your health condition as well as your age.

        You can’t do anything about the first and last aspect, but it seems that to some extent we have our fortunes in our own hands, quite separately from taking such precautions as social distancing and hand washing etc.

        Incidentally nic, I have never had a clear idea as to the best condition for our homes as we approach autumn and winter. Should we have warm homes and a high humidity, cool homes and a low humidity?

        I think the well ventilated bit we can take as read

        Tonyb

      • Warm and high relative humidity is generally preferable, as far as I am aware.

      • Robert Starkey

        Nice

        Doesn’t the virus live longer on surfaces in higher humidity?

      • Robert Starkey

        Nic
        Sorry. Assuming it does live longer on surfaces in higher humidity, it’s complicated indoors in winter. Dryer humidity increases air transmission but…

      • If I was at high risk I would have a recirculating air filter unit with HEPA filtration and UVC sterilization. That or fresh air makeup is the best defense against aerosolized virus in a closed space IMO. There are some residential heat exchangers that provide air turnover without too much loss of heat also.

    • “This means that the immune systems of people with type A blood develop antibodies for B antigens, people with type B blood have antibodies for A antigens, and people with type O blood have antibodies for both. Blood type influences blood clotting, and a growing body of evidence suggests that COVID-19 pathology often involves overactive blood clotting. People with type O blood have lower levels of proteins that promote blood clotting.
      SARS-CoV-2 can replicate in cells that express blood type antigens, Jacques Le Pendu, a glycobiologist at the University of Nantes told Chemical and Engineering News. This means that when an infected person coughs or sneezes, there’s a possibility that they release viral particles coated with their blood type antigens.
      Explained more in depth, a person in the blood type O group will have antibodies against virus transmission from someone in the blood type A group, which can fight the virus. However, a person in the blood type A group won’t have those same antibodies.”

      Continuing the theme of baseline immunity existing 2 years ago and now. Lowering effective herd immunity. No immunity 2 years ago? Got it.

    • Relative vs. absolute risk is a relevant factor here.

      And it should have little to no impact on policies or behaviors.

  8. Here’s what I think you’re saying. Some people can have it and are very weak transmitters. That they have it is providing them with immunity. A weak transmitter lowers effective herd immunity. Look at a nursing home. An old person has it a lot and is a raging transmitter, who makes other raging transmitters and we get a death flash wave. (Then it’s blamed on Trump.) Where are the stories of a household being taken out and all are in the an ICU? Children are weak transmitters. Schools. Homes are what? One or two parents and children.

    I have been following this more than your average bear. Can you sum your main points up for marketing please? Nic, your audience is the world and you can do it.

    • The key point is that cross-reactive T cell memory is likely to be a source of variability between individuals in their biological susceptibility to being infected by SARS-CoV-2, alongside other factors such as innate immune system strength, genotype and age, providing one takes an operational definition of infection. By that, I mean defining infection as involving the development of symptoms and/or non-negligible infectivity, not as just involving at least one cell having been invaded by the virus.

      Lipsitch et al.’s illustration of their model scenario 3 suggests that, while no symptoms would occur, infectivity – although greatly reduced by cross-reactive T cells – would not be rendered negligible. However, this does not take into account the level of the viral dose, which will vary from one exposure to potential infection to another. There must come a point, at a lower viral dose level, when under this scenario the extent of viral replication reduces so much infectivity does become negligible, while it would not be negligible in the absence of cross-reactive T cells.

      The effect of cross-reactive T cells, in increasing variability between individuals in their biological susceptibility to being infected by SARS-CoV-2, and thus lowering the herd immunity threshold will not be taken into account in estimates thereof based on early epidemic growth and standard epidemiological models, contrary to the assertion by Lipsitch et al.

      Lipsitch et al. and I both focus on the possible protective effect of cross-reactive T cells. However, the implications for the herd immunity threshold (relative to that estimated from early epidemic growth) of their having the opposite effect, of making people more vulnerable to infection by SARS-CoV-2, would be similar. That is because such an effect would also increase variability in biological susceptibility, and it is the variability therein (along with variability in social connectivity/contact rates), not its average level, that determines the extent of overestimation of the herd immunity threshold when using early epidemic growth data.

  9. Pingback: T cell cross-reactivity and the Herd immunity threshold |

  10. Judith, please take Climate etc. back to what it once was. Nic Lewis’ thoughts and ideas are probably interesting to people who do not know a cat’s ass about virology, epidemiology and general sociology.

    Nic Lewis’ posts are at Tony Heller level dressed in a scientific suit. Neither Nic Lewis nor any of these Covid deniers have understood that the subject is not to count the dead on a fortnight basis.

    • Robert Starkey

      Rune

      What is a “covid denier”? Are there people who don’t believe that any covid virus exist or just covid 19.

      You could disagree with Nic’s statistical analysis or the specific conclusions he has reached based on his statistics, but choose otherwise.

      • What is a “covid denier”? They come in many shapes, here is one:

        Stockholm will achieve herd immunity by end af May is another variant.

        What many seems not to understand is that if this epidemic is not kept in check, it is only a matter of time before the hospitals become overcrowded and the health care system is blown up. In Spain, people died on the floor in hospital corridors, in many cases younger people who probably should have survived.

      • Robert Starkey

        Rune

        So in your world, being wrong about at what rate HIT is achieved makes a person a covid denier?

        Imo you inappropriately use a hostile term as a part of a rant when the science of when HIT will be ultimately achieved in various countries is unknown.

    • Rune –

      I’m not sure what high quality days of yore you’re pining for. Here’s a link to four years ago, comments from jim2, AK , and ciscokid. All regular commenters at the time. Zero pushback from the rest of the regulars.

      https://judithcurry.com/2016/07/29/week-in-review-politics-edition-4/#comment-800836

      Seth Rich level conspiracy ideation has been a mainstay of Climate Etc. for a very long time.

      Anything that’s remotely political (and practically everything is) brings out this level of reasoning.

      • Perhaps you could apply for the job of moderator. Then you could filter stuff out so we poor souls are not at risk of being sullied by it. The generosity and sacrifice on your part by assuming this burden on behalf of the community would be nothing short of saintly.

        Rune was complaining about a blog post by a contributor, and you dig up random comments (not by him) from four years ago in affirmation. No matter how much they vexed you at the time, you really should have got over it by now.

      • > No matter how much they vexed you at the time, you really should have got over it by now.

        What is it that I need to get over? I enjoy reading the crazy conspiracy comments here. Always have. Enjoyed it then. Enjoy it now. They’re funny.

      • aporiac –

        I ejoyed them then, I moved on to enjoy the more recent series of wacky conspiracy theories oriole post here (some be the same crew). Rune mentioned a deterioration in quality so I used the Google for Seth Rich mentions here. Shockingly, I found as some. You’ve heard of the Google, havd you?

        So I enjoy them now, and offer them for your enjoyment as well. So take that gift and quit while you’re behind.

      • Well, you are half right. Those are quotes from an article in my case, not my original thoughts. The title of the blog is Climate, Etc. Not Climate, the-way-Rune-and-Joshua-like-it.

    • Rune Valaker: Neither Nic Lewis nor any of these Covid deniers have understood that the subject is not to count the dead on a fortnight basis.

      Do you have any criticisms of any specific propositions? Do you have any examples from here of “Covid deniers”?

  11. “The authors say that evidence for other human coronaviruses makes this implausible, and that when epidemiological evidence of very high attack rates in some ship-based outbreaks is added scenario 4 is highly unlikely.

    However, in the most studied ship-based outbreak the proportion infected was under 20%.[4] ”

    Diamond princess? again?
    to be favored because its the Most studied?

    Look Nic, there are other ship studies where the attack rates are above 20%
    even 100%.
    There are prison studies with attack rates well over 50%
    In recent work on Tokyo, a prevalence of 46%

    quit ignoring data

    Sumter Correctional Institution 62%
    Tomoka 60 %
    San Quentin 68%
    Eddie Warrior 72%

    and there are more, you never look for data to challenge your hypothesis

    Diamond princess fans never do.

    • 9/28 article:

      Six prisons have reported no cases, and the average inmate infection rate across all prisons is 4%. Snake River’s infection rate among its 2,700 inmates is 14%, second only to Eastern Oregon Correctional Institution in Pendleton, where 18% of inmates have been infected.

      https://www.eastoregonian.com/coronavirus/covid-19-infections-at-srci-nearly-double-in-one-month/article_c0a2252e-019c-11eb-87c5-03688f080ce0.html

      Do you have any links to back up your claims, Mosh?

      • https://www.cdc.gov/mmwr/volumes/69/wr/mm6926e2.htm

        Seventy-one additional cases of SARS-CoV-2 infection were detected in the five dormitories. Among 98 persons tested on day 1, 53 (54%) had positive SARS-CoV-2 test results (Table 2). Among the remaining 45 who had negative test results on day 1, 16 (36%) had positive test results on day 4. Two (7%) of 29 persons who had negative test results on days 1 and 4 had a positive test result on day 14. Of the 71 cases, three (4%) occurred in persons who were presymptomatic at the time of specimen collection, 29 (41%) were in persons who were asymptomatic, and two (3%) were in persons who had had unknown symptom histories. Among the 37 patients who reported COVID-19 symptoms before testing, 11 (30%) reported symptom onset ≤2 weeks before testing, and 19 (51%) experienced symptom onset >2 weeks before testing. Among 27 persons testing negative, 18 (67%) reported COVID-19–compatible symptoms in the previous 2 months, including eight (30%) reporting loss of smell and seven (26%) reporting loss of taste. Among the 98 persons who were tested, 55 (56%) reported at least one COVID-19 symptom during the 2 months before testing, including 37 (52%) who had positive test results and 18 (67%) who had negative test results. Headache (27, 38%) and loss of smell (25, 35%) were the most commonly reported symptoms. During the public health outbreak investigation period, none of the COVID-19 patients identified through serial testing developed severe illness requiring hospitalization.

        The attack rate by dormitory ranged from 57% in dormitory A to 82% in dormitory C. The number of days between the first identified COVID-19 case in each dormitory and day 1 testing ranged from 14–30 days. Dormitory A, which had the lowest attack rate, also had the shortest interval from day of first COVID-19 case to day 1 testing.

      • Seventy-one additional cases of SARS-CoV-2 infection were detected in the five dormitories. Among 98 persons tested on day 1, 53 (54%) had positive SARS-CoV-2 test results (Table 2). Among the remaining 45 who had negative test results on day 1, 16 (36%) had positive test results on day 4. Two (7%) of 29 persons who had negative test results on days 1 and 4 had a positive test result on day 14. Of the 71 cases, three (4%) occurred in persons who were presymptomatic at the time of specimen collection, 29 (41%) were in persons who were asymptomatic, and two (3%) were in persons who had had unknown symptom histories. Among the 37 patients who reported COVID-19 symptoms before testing, 11 (30%) reported symptom onset ≤2 weeks before testing, and 19 (51%) experienced symptom onset >2 weeks before testing. Among 27 persons testing negative, 18 (67%) reported COVID-19–compatible symptoms in the previous 2 months, including eight (30%) reporting loss of smell and seven (26%) reporting loss of taste. Among the 98 persons who were tested, 55 (56%) reported at least one COVID-19 symptom during the 2 months before testing, including 37 (52%) who had positive test results and 18 (67%) who had negative test results. Headache (27, 38%) and loss of smell (25, 35%) were the most commonly reported symptoms. During the public health outbreak investigation period, none of the COVID-19 patients identified through serial testing developed severe illness requiring hospitalization.

        The attack rate by dormitory ranged from 57% in dormitory A to 82% in dormitory C. The number of days between the first identified COVID-19 case in each dormitory and day 1 testing ranged from 14–30 days. Dormitory A, which had the lowest attack rate, also had the shortest interval from day of first COVID-19 case to day 1 testing.

      • “An Arkansas county so rural it has just three incorporated towns and not a single stretch of interstate suddenly emerged this week as one of the nation’s coronavirus hotspots. Ground zero in Lincoln County, about an hour’s drive south of Little Rock, is the Cummins Unit, a state prison farm known for producing cotton, rice and eggs.A farm employee was the first to test positive in early April. Now 14 staffers and more than 680 of the prison’s nearly 1,700 prisoners have the virus, according to test results reported this week.”

      • “When coronavirus cases began to spike at North Carolina’s Neuse Correctional Institution, 60 miles southeast of Raleigh, prison officials took the opposite approach, testing all 700 inmates and 250 staff.They found at least 65 percent of the prisoners have the virus, a number that may increase as all results come in. Notably, 98 percent of those infected were not showing symptoms, said John Bull, a corrections department spokesman.”

      • Steven Mosher

        San quentin

        https://www.cdcr.ca.gov/covid19/population-status-tracking/

        Did you think that I did not check?

        Look Nic never checked the diamond princess Strain.
        The less infectious D614 strain.
        I checked, I always check.
        Nic didn’t check all the ship cases… shall we start that route as well

        he didn’t check prisons.

        WHY?

        because he has to believe the diamond princess.

      • Steven Mosher

        https://www.iflscience.com/health-and-medicine/mysterious-covid19-outbreak-on-ship-after-35-days-at-sea-stumps-scientists/

        ‘Argentina is currently dealing with a mysterious Covid-19 outbreak onboard a ship that’s been out at sea for over 35 days. Considering all the sailors tested negative and self-quarantined before they set sail, no one is quite sure how the virus came aboard and infected dozens of crewmembers.

        At least 57 out of 61 people onboard the Etchizen Maru fishing trawler have tested positive for Covid-19, according to local health authorities in Argentina’s southernmost province of Tierra del Fuego in Patagonia. Two of the crew have tested negative, while the remaining two are still awaiting confirmation of their results. ”

        Somebody get those guys some cross reactive T cells.

        cause 61 tested negative before sailing
        and now 57 of 61 have tested positive.
        (index case was probably a 80 year old man they shared a plane with
        just prior to boarding the ship)

        Ignore this because Nic will

      • Steven Mosher

        Another reason why it is dumb to focus on the diamond princess

        https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326407/

      • Steven Mosher

        another ship 85%
        if you want to check for the genetic isolates be my guest
        I would bet its SG614
        Ascension numbers are USA/WA-UW-10027/2020 -USA/WA-UW-10138/2020 in the GISAID

        https://www.medrxiv.org/content/10.1101/2020.08.13.20173161v1

        85%

        Predeparture serological and viral RT-PCR testing along with repeat testing after return to shore was available for 120 of the 122 persons on board over a median follow-up of 32.5 days (range 18.8 to 50.5 days). A total of 104 individuals had an RT-PCR positive viral test with Ct <35 or seroconverted during the follow-up period, yielding an attack rate on board of 85.2% (104/122 individuals).

        Nic will ignore this data

      • Steven Mosher

        You see jim if there were this magic fairy dust cross reactivity
        you would not see countless types of situations, locations, and events
        with high attack rates.

        https://www.cdc.gov/mmwr/volumes/69/wr/mm6920e2.htm

        At the bottom Nic mistake is trying to use one R0.
        we’ve know for years this is an over simplification.

    • They also never look at the halotypes of the diamond princess virus

      https://www.medrxiv.org/content/10.1101/2020.03.23.20041970v1

      hint: ??? less infectious genetic isolate SD614 ( early Asian strain)
      10x less infectious

      https://www.biospace.com/article/mutated-covid-19-viral-strain-in-us-and-europe-much-more-contagious/

      In short

      By looking at the attack rate of the diamond princess you are
      BIASING your analysis because princess is the D614 strain of the
      Spike protein ( SD614)
      which is less infectious ( lower R0)

      You can see the japan data (genetic strains) here.

      https://nextstrain.org/ncov/asia?c=gt-S_614&dmax=2020-04-13&f_country=Japan&f_division=Japan&s=Japan/DP0184/2020

      only two samples of SG614, and the diamond princess was SD614
      as published

      Like I said before Diamond princess is junk, pretty much useless.

      psst deaths are up to 14 out of 712 ( as predicted)

    • Steven Mosher: Diamond princess? again?
      to be favored because its the Most studied?

      quit ignoring data

      I don’t think that Nic’s point is that attack rates are uniformly low but that they are sometimes (many times?) low, and (1) the variability has to be taken into account in modeling and (b) the mechanisms contributing to low attack rates are not fully understood.

      Attack rates are sometimes high as well. Something that might be called a “representative” attack rate, or mean attack rate, or median attack rate isn’t known, even for reasonably circumscribed areas like Stockholm or Los Angeles.

    • Steven,
      I do not get the gist of your argument, if there is one.
      Granted there are different strains of the virus with different infectivity rates.
      Part of the reason the Australian experience is so different to the Swedish.
      Good of you to note this.
      Granted there are countless examples of differing infective rates on ships, jails countries etc.
      Needs to be noted as well
      Granted Nic has upset the applecart of theories on ECS etc of a couple of your scientifically sloppy friends.
      Being nice to your friends.
      Where exactly is your beef with T cell cross-reactivity and the Herd immunity threshold?
      Nic has proposed a theory on herd immunity putting forward reasons for why one country, Sweden may have a much lower herd immunity threshold than expected. Not every country.
      You are putting up red herrings about different infective rates which Nic is fully aware of.
      Why don’t you discuss the premise of the infection threshold, the super spreader concept, and the figures he quotes to either support or refute his specific claims on herd immunity?
      Show your expertise rather than the niggled side.

  12. “The first point to make is that cross-reactive T cells were never thought to be the main cause of the herd immunity threshold (HIT)[2] being lower for COVID-19 than the oft-quoted {1 – 1/R0} level, which generally applies for vaccination.”
    Vaccination develops antibody cells [B cells,] it also activates the T4/8 systems. The point being that it is the antibodies that develop in response to a new infection that interact with the virus particles helping block attachment and identifying the virus as a FB which needs to be destroyed.
    The antibody presumably also provides a starting point for the chomping cells to start chomping, without destroying other proteins and components of the surrounding tissue and blood.
    T cells have no place in viral destruction. T4 cells identify and help destroy infected cells stopping belatedly further production and offering the B cell antibodies access to the viral particles to bind with them, inactivate them and hopefully make them indentifiable and capable of being destroyed.
    Activated T cells have no useful purpose or role without an antibody to attack the virus.

  13. Hello, Nic Lewis,
    I have been following your post for some while now. I have found them very interesting. I hope you keep up the great work.
    I have, nontheless a question. I am reading some doctors who say the initial viral content of an infection, doesnt have much impact on its repercusion. Patients may present severe simptoms from mild exposition to the virus, and viceversa. The say this is not specific for COVID-19 but pretty much established in the medical comunity.
    I am no expert in this, so I wonder, have you got any insight on this issue? You mention viral load as a meaningfull variable. ¿Do you have some reference to back it up?
    Thank you, very much

  14. Nic

    Have you seen this very interesting article by Mike Yeadon?

    https://lockdownsceptics.org/what-sage-got-wrong/

    It covers herd immunity and the composition of SAGE which appears to be comprised of people of little direct relevance to the subject they are being asked to advise on

    Tonyb

    • W/r/t the appeal to authority in regard to Ioannidis paper on fatality rate (and no mention of views other well qualified analysts). I have yet to see any response to what seems to me to be sound skepticism.

    • From the article.

      > (which, btw, has always happened)

      How many months have we seen these pronouncements being made? I remember David Young making such pronouncements here a couple of months ago.

      What’s funny to me about these ridiculously certain pronouncements in the face of such vast uncertainties is that it is largely being made by the sane crowd who hide behind uncertainties when the topic of climate change comes up.

      That it also happens from the crowd that ignores the uncertainties in projections in the Covid context, to do things like mischaracterize the IC projections, is only icing on the cake.

      If you know what I’m talking about, Tony.

      • Oops – wrong thing left in the cache. That should have started with…

        > If I am correct, the pandemic is weeks from being completely over and is already done and dusted everywhere south of the Midlands (with the possible exception of Wales

      • Joshua

        Unlike the climate uncertainties that rely on forecasts for events in a century we shall know by the end of November if in effect the virus has blown itself out In the south

        Tonyb

      • I see. Tony. So you’ve worked out all the uncertainties beyond that, eh?

        You know, lots of people thought they had dkne so here also. They told us months ago that the surge in infections was only because of more testing and more young people getting infected. But was over, they said. Before that, they were sure it would die outnjnce it for warm. Disappear by Easter, some said. Some famous ones like Michael Levitt who gets a lot of focus I’m the right wing, libertarian, crowd. Then the deaths went up also after the predicted lag. Most got a bit quite after that. At least for a bit (although it didn’t slow Levitt down one bit). But for others, clearly accountability is clearly no big deal.

        Disrespect Mr. Uncertain T. Monster if you wish, Tony. Me? I’ll wait ’til the fat lady sings.

    • Tonyb
      I’ve now seen that article. What it says about SAGE doesn’t surprise me at all, but I haven’t verified it.

    • I know I am really bad at math because these folks confidently assert that the IFR is 0.2%, and we’d reach a HIT at 20% (if not lower) – and my calculator tells me that would work out to reaching a HIT once we reached 132,000 deaths in the US (0.2% of 66,000,000 infections). And that it happened about 4 months ago.

      Now I know that the theory is that there’s “overshoot” and that deaths don’t just stop when a HIT is reached, but 4 more months of rapid spread and an additional 90k deaths or so (and counting) over four months would suggest to me there something wrong with their logic. And since they’re clearly much smarter than I, there just has to be something wrong with my math.

      For the UK it would mean they reached a HIT at about 27k, five months ago.

      Clearly I am really bad at math.

  15. This is interesting…

    > What we can conclude from this is that SAGE is wrong to rely on percentage seroconversion (antibodies) as a reliable guide to the proportion of the population who’ve been infected. This is a truly dreadful error, one that could not have been made but for the inadequate skillsets of the members of SAGE.

    So after appealing to Ioannidis’ authority, he puts Ioannidis into the group of people whose skills set is so lacking that they’d make such an obvious and “dreadful” error (not to mention Bhattacharya and the whole Santa Clara research team).

  16. I have stated this before but I will repeat it once again. What Nic and all the other covidsceptics do not understand is that there is a fine line between what the health service can handle and when there will be chaos and total collapse. Italy and Spain had these collapses in April / May when otherwise vigorous people died completely unnecessarily due to lack of capacity. In Sweden, they made a brutal choice, people over a certain age who became infected, were put straight on palliative care without even trying IC or respirators. Swedish health workers are exhausted after seven months of trying to achieve herd immunity, while the numbers per. October 16, several months after herd immunity should have been reached in Stockholm, now more than suggests a new round of massive pressure on the health care system.

    What was socially acceptable in 1920 during the Spanish flu, a few years after millions of teenagers had become meaningless victims during World War I, is not acceptable today. And that is among the valuations Nic and other Kovid skeptics do not include in their calculations, or should we say models.

    • Robert Starkey

      It seems your point is that government should closely monitor “hospital utilization” vs “hospital capacity” and have plans to ensure capacity is not exceeded as a result of covid 19.

      In the US this has not been a problem. The problem with US hospitals currently is that many are loosing money due to under use.

    • Rune

      You don’t need to go back to the Spanish flu to observe high death numbers in Sweden . Here are ‘excess’ deaths.

      https://emanuelkarlsten.se/number-of-deaths-in-sweden-during-the-pandemic-compared-to-previous-years-mortality/

      In my lifetime in the Uk I have Lived through some four worse epidemics than today, especially if our expanding population is taken into account . Which is not to say of course that the current pandemic is not serious.

      Arguably flu is more serious as it happens every year and we should therfore be compelled to wear masks etc and take similar precautions to those for covid.

      I am hoping nic can give us an opinion on the link I provided above which seems to be an interesting study in herd immunity

      Tonyb

    • Rune. “vigorous people died completely unnecessarily due to lack of capacity.”
      Vigorous people do not die.
      “In Sweden, they made a brutal choice, people over a certain age who became infected, were put straight on palliative care without even trying IC or respirators. Swedish“

      Brutal, meaning you wish to disparage someone so choose an ugly word?
      Choice of medical treatment always involves making decisions on whom to treat and when to treat.
      In Norway, every day for the last 20 years, doctors and families made decisions to put people on palliative care not because they are brutal Norwegians but a decision had to be made whether it was kinder, more compassionate to stop or withhold treatment given that it would cause pointless pain and suffering to keep them alive.

      It is not a brutal choice, it is a Sophie’s choice, palliation is recognition that in a no win situation one option is much kinder and gentle, easing suffering than the brutal option you espouse.

    • Steven Mosher

      “I have stated this before but I will repeat it once again. What Nic and all the other covidsceptics do not understand is that there is a fine line between what the health service can handle and when there will be chaos and total collapse.”

      Yup
      it does not fail over easy

    • “the numbers per. October 16, several months after herd immunity should have been reached in Stockholm, now more than suggests a new round of massive pressure on the health care system.”

      Where’s your evidence? I haven’t spotted any significant rise in Swedish intensive care admissions, which appears to be the main capacity limit of their health system (Sweden has a far lower number of ICU beds per head than the UK, which in turn has far fewer than some other European countries).

      “Swedish health workers are exhausted after seven months of trying to achieve herd immunity”

      Where’s your evidence? Hospital and ICU COVID occupancy appears to have been low since late spring. And total case numbers were quite low until recently.

      • Steven Mosher

        case numbers increased after you declared herd immunity.

      • Could just be “overshoot.” Looking less likely though. Or maybe the 4 x increase in infection rate will just end. Or maybe it’s just young people who are getting sick and tested (rember when yhey said that when Arizona and Florida and Texas spoked)?

        Or maybe Nic has some herd immunity magic fairy dust and a 4 X increase in cases rate won’t result in increases in hospitalizations. One can always hope so.

      • That said, just took a tour around Worldometers. Cases up dramatically in many countries, but for the most part deaths up only a little in almost all. Maybe something fundamental really has changed.

        And now, there’s this – which independent of the distribution of a vaccine and with the article that ragnaar recently linked really suggests good news and dramatic improvements in treatment going forward.

        https://scitechdaily.com/johns-hopkins-researchers-identify-immune-system-pathway-that-may-stop-covid-19-infection/

  17. The big “Solidarity” international COVID drug study has just reported results – the drugs don’t work. Four treatments were tested:
    remdesivir,
    hydroxychloroquine,
    lopinavir/ritonavir,
    interferon

    None of them improved hospital outcomes in terms of deaths, days on oxygen and recovery time.

    So to date it’s only dexamethasone that improves survival and severe covid19 disease outcome.

    https://www.cnbc.com/2020/10/16/who-remdesivir-has-little-or-no-effect-in-reducing-covid-19-deaths.html#close

  18. An interesting juxtaposition that ice pointed to many times:

    -snip-

    Many of those who have praised Sweden’s “freedom-loving” strategy on coronavirus were the same people aghast at its liberal immigration policy in 2015. Some in Sweden see little to link the two. But for others there are more subtle ties.

    Mr Tegnell told the Financial Times in August that the concerns around both crises may be overblown: “The migration crisis wasn’t really a crisis. We absorbed those people and, of course, we are not the best country in the world in integrating them and, of course, they are still a problem. But it’s not a major problem. The economy went on living. The housing situation did not change very much.”

    -snip-

    Add to that the euthanasia-like healthcare “rationing” and nationalized healthcare that Sweden employed with sick older people to limit spread in their hard-pressed healthcare institutions – that would have the American rightwingers who suddenly love them some Swedish public policy, pearl-clutching about soshlism and “death panels” if any of that was employed here.

    https://amp.ft.com/content/71c8a636-4d40-4d0e-947f-af8de9b6b82c

  19. snip-

    Many of those who have praised Sweden’s “freedom-loving” strategy on coronavirus were the same people aghast at its liberal immigration policy in 2015. Some in Sweden see little to link the two. But for others there are more subtle ties.

    Mr Tegnell told the Financial Times in August that the concerns around both crises may be overblown: “The migration crisis wasn’t really a crisis. We absorbed those people and, of course, we are not the best country in the world in integrating them and, of course, they are still a problem. But it’s not a major problem. The economy went on living. The housing situation did not change very much.”

    -snip-

    • Many of those who have praised Sweden’s “freedom-loving” strategy on coronavirus were the same people aghast at its liberal immigration policy in 2015. Some in Sweden see little to link the two. But for others there are more subtle ties.

      • “…Tegnell told the Financial Times in August that the concerns around both crises may be overblown: “The migration crisis wasn’t really a crisis. We absorbed those people and, of course, we are not the best country in the world in integrating them and, of course, they are still a problem. But it’s not a major problem. The economy went on living. The housing situation did not change very much.”

        -snip-

      • Add to that the euthanasia-like healthcare “rationing” and nationalized healthcare that Sweden employed with sick older people to limit spread in their hard-pressed healthcare institutions – that would have the American rightwingers who suddenly love them some Swedish public policy, pearl-clutching about soshlism and “death panels” if any of that was employed here.

        https://amp.ft.com/content/71c8a636-4d40-4d0e-947f-af8de9b6b82c

        There’s a good quite from tTegnell in that passage also that won’t get past the moderation filter for some odd reason.

      • I hit a paywall on that link, sigh.

  20. Steven Mosher

    Nic:
    “Very sensibly, the Swedish public health authority has surveyed the prevalence of infections by the SARS-COV-2 virus in Stockholm County, the earliest in Sweden hit by COVID-19. They thereby estimated that 17% of the population would have been infected by 11 April, rising to 25% by 1 May 2020.[5] Yet recorded new cases had stopped increasing by 11 April (Figure 1), as had net hospital admissions,[6] and both measures have fallen significantly since. That pattern indicates that the HIT had been reached by 11April, at which point only 17% of the population appear to have been infected.

    How can it be true that the HIT has been reached in Stockholm County with only about 17% of the population having been infected, while an R0 of 2.0 is normally taken to imply a HIT of 50%?”

    Facts: HIT has NOT been reached in

    but

    • Stephen, according to the CEBM, the main reason we are seeing increased “cases” is because of the increased testing, and because the PCR detects the viral remnants – NOT the actual virus itself. These RNA remnants can remain on the body (in airways etc) for weeks even months. So it’s likely the “second wave” is at least partly spurious. People are coming into contact with the virus, and either destroying it themselves, or picking RNA particles from people who have.

      The second part of your post alludes to this, and does not – necessarily – contradict Nic’s assertion that HIT has been reached. The reason is pointed out in Nic’s OP, it depends on how you define “infection”. The PCR test is very sensitive, and is picking up a lot of asymptomatic people. This would be the case with a vaccine as well – vaccines increase resistance, to the point that people who are “infected” can be asymptomatic, but they can still be very mildly infectious.

      What appears to be happening is that the virus is more wide spread than previously thought, but people have been getting low viral loads and developing immunity, and/or they have sufficient natural resistance such that the illness is trivial, and this would qualify as Herd Immunity…at least as Nic puts it “operationally” immune.

      There is only so much the PCR test can tell you. The best indication of HIT is probably through hospitalisation.

      • agnostic –

        > Stephen, according to the CEBM, the main reason we are seeing increased “cases” is because of the increased testing, and because the PCR detects the viral remnants – NOT the actual virus itself.

        The positivity rate is increasing. The tests haven’t gotten more sensitive. Increased testing is likely partially explanatory, but also not fully explanatory as you confidently assert – with no respect for uncertainties.

        Also:

        > An increased concentration of the virus in wastewater, the KTH researchers write, shows a rise of the virus in the population of the greater Stockholm area (where a large proportion of the country’s population live) in a way that is entirely independent of testing.

        https://www.kth.se/aktuellt/nyheter/avloppsvatten-visar-stor-okning-av-covid-19-i-stockholm-1.1016275

        Tegnell says they haven’t reached “herd immunity” status.

        -snip-

        “I think the obvious conclusion is that the level of immunity in those cities is not at all as high as we have, as maybe some people have believed,” he said.

        “I think what we are seeing is very much a consequence of the very heterogeneous spread that this disease has, which means that even if you feel like there have been a lot of cases in some big cities, there are still huge pockets of people who have not been affected yet.”

        -snip-

        https://www.businessinsider.com/sweden-shifts-away-no-lockdown-strategy-amid-growing-case-numbers-2020-10

      • There may be any number of reasons why the rate of hospitalizations and deaths in Sweden have it tracked with the increased rate of infections, as if yet.

        At what point does, say, a huge increase in infections in Stockholm falsify Nic’s assertion a that they reached a “herd immunity threshold” there 5 months ago? In an increase of some 400% over the past few weeks doesn’t do it, what numbers would? Post-hoc rationalizations based on a lack of increase of serous infections doesn’t do it. The “herd immunity threshold” status was based on a theoretical assertion related to rate of infections.

      • Sorry. You did acknowledge some uncertainty. But you also confidently assert a “main reason” (by way of CEBM) that ignores uncertainties.

    • “At what point does, say, a huge increase in infections in Stockholm falsify Nic’s assertion a that they reached a “herd immunity threshold” there 5 months ago? ”

      The point would be when the detections are CONFIRMED as covid, not merely as detections. It’s important to remember that the PCR only detects REMNANTS of the virus NOT the actual virus itself. By concentrating on the detections, it may give an incorrect account of what is really going on.

      Either you need to culture the virus from subjects, or wait to see if there are increasing hospitalisations. There has been an increase (at least in the UK) where ever we have seen second wave, but only a fraction of what we saw in the first wave. So at least some herd immunity – which is never a perfect thing – has been achieved.

      The important thing is to make sure the response is proportionate. No one is proposing nothing be done, but it’s not just lives at stake, it’s livelihoods.

      I have to stress, I don’t see much acknowledgement in these discussions that the PCR test only detects the PRESENCE of viral material – and no acknowledgement that it says nothing about whether the subject was infectious, or ill.

  21. “How can it be true that the HIT has been reached in Stockholm County with only about 17% of the population having been infected, while an R0 of 2.0 is normally taken to imply a HIT of 50%?”

    “The effective reproduction number, Re, sometimes also called Rt, is the number of people in a population who can be infected by an individual at any specific time. It changes as the population becomes increasingly immunized, either by individual immunity following infection or by vaccination, and also as people die.
    Re is affected by the number of people with the infection and the number of susceptibles with whom infected people are in contact. People’s behaviour (e.g. social distancing) can also affect Re.
    Unfortunately, the symbol R0 is often used in publications when Re is meant. This can be confusing.
    Herd immunity
    R0 predicts the extent of immunization that a population requires if herd immunity is to be achieved, the spread of the infection limited, and the population protected against future infection. To prevent sustained spread of the infection the proportion of the population that has to be immunized or have had the infection (Pi) has to be greater than 1 − 1/R0.”

    This is proposing a truly naive population with homogeneous susceptibility and spread and ability to spread.

    “How can it be true that the HIT has been reached in Stockholm County with only about 17% of the population having been infected, while an R0 of 2.0 is normally taken to imply a HIT of 50%?”
    o
    I believe that Nic is stating his ideas on the basis, Mosher, that the population is not homogeneous, not naive, not equally spread and that the spread of the virus is not equal.
    You should know that.
    Hence why his R0 differs from the expected R0.
    And why the Re differs with each scenario.
    Stick to the script, son.

  22. -snip-

    I think the obvious conclusion is that the level of immunity in those cities is not at all as high as we have, as maybe some people have believed,” he said.

    “I think what we are seeing is very much a consequence of the very heterogeneous spread that this disease has, which means that even if you feel like there have been a lot of cases in some big cities, there are still huge pockets of people who have not been affected yet.”

    -snip-

    https://www.businessinsider.com/sweden-shifts-away-no-lockdown-strategy-amid-growing-case-numbers-2020-10

  23. Matthew R Marler

    Right now there is some sort of message developing in the spread of the disease in Brazil, Argentina, Chile, Peru, Colombia and Mexico. Not just the European nations like Spain. Maybe also in India where the disease is spreading at a below exponential but non-negligible rate.

    The US is now conducting about 1.1 million tests per day, with looser exclusion criteria than last winter and spring, and turning up large numbers of positives with very low and (presumably) safe titers. So case counts are increasing faster than death counts (maybe treatments are better as well); death counts are not growing exponentially, but if rate of growth is declining it does not seem to be declining rapidly.

    Next up: what will happen with the onset of cold weather?

    • Where are you getting info on the titers among those who tested positive? Have you seen data on cycle threshold values?

      > Next up: what will happen with the onset of cold weather?

      Indeed. More people in close quarters, at lower humidity and less fresh air circulating, for longer period of time. Can only hope that the apparent trend of divergence in the ratio of infections to hospitalizations and deaths continues.

      • What exactly is an apparent trend?
        Why is it always trending in the opposite way to what we wish or expect?
        Pauses can do the same thing.
        Apparently.
        Perhaps the word apparently can give us a barometer on our unconscious biases.
        I don’t expect the trend to catch on.
        It is food for thought though.
        Apparently

  24. Herd immunity is a ultimately a myth that has been used as a rationale for vaccines. This discussion is moot, thankfully. Herd immunity is off the table.

    First, while the object of study, cross-reactive T cells appear to no functional involvement in either infectivity or pathogenesis of SARS2

    Given the fact that the protective immunity conferred by a SARS2 infection is shorter (< 90d) than the pandemic episode there will always be waves. Witness what is going on in the EU currently. Add to that, sterilizing immunity is not possible, While protected the infected are infectious.

    The Covid-19 is an immunopathology. When Trump was given the cocktail of mono-clonal antibodies, at a time when he slipping into a severe state, he was sero-negative for Sars2 Ab's.

    This should also guide one's vaccine choice. I wouldn't think that one would want the viral genome introduced in any way. But then, no vaccine will perform better that our body's response to a natural infection. The vaccine is a non-starter.

    I am betting on blockers.

    Good luck to us all.

  25. (Ooops and no edit)

    one would NOT want the viral genome introduced

  26. Hospitalizations still in a downward trend:

    https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

    • > Hospitalizations still in a downward trend:

      Hmmm.

      Actually, upward trend pretty much in perfect synch with trend of increase in positive tests:

      https://covidtracking.com/data/charts/us-currently-hospitalized.

      Deaths starting to track upward with the predicted six week lag in upward trend in positive testing. This is a repeat of when “conservatives” said that the spike this summer was only due to more younger people getting tested and more peope getting tested ginky to see deaths spike 6 weeks after the positive tests spiked.

  27. Ivermectin, wonder drug for the ages?

    From 2012 onwards, there have multiple reports that ivermectin has antiviral properties [4,5,7,8,9,10,11,12,13,14,15,16,17] towards a growing number of RNA viruses, including human immunodeficiency virus (HIV)-1, influenza, flaviruses such as dengue virus (DENV) and Zika virus (ZIKV) and, most notably, SARS-CoV-2 (COVID-19) [17].

    https://www.mdpi.com/2073-4409/9/9/2100/htm

    • Jim2: Ivermectin is almost certainly not potent enough at inhibiting the growth of SARS-CoV-2 to be useful in treating humans. The data below compare the concentrations needed to inhibit viral replication in a cell culture experiment with the concentrations usually found in the blood after dosing. In the case of Remdesivir, peak blood levels are almost 10X HIGHER than the cell culture IC50 (Concentration the Inhibits growth by 50%) – and Remdesivir is only marginally useful in treating COVID. Likewise Tamiflu and related drugs have IC50’s in at least an order of magnitude lower than than peak blood levels. For drugs that treat HIV, the difference is even larger.

      “Caly et al.10 report a 5,000-fold reduction in SARS-CoV-2 RNA levels, compared with those in controls, after infected Vero/hSLAM cells were incubated for 48 hours with 5 μM ivermectin. The ivermectin IC50 for the virus was calculated at approximately 2.5 μM. These concentrations are the equivalent of 4,370 and 2,190 ng/mL, respectively, notably 50- to 100-fold the peak concentration (Cmax) achieved in plasma after the single dose of 200 μg/kg (14 mg in a 70-kg adult) commonly used for the control of onchocerchiasis.12 Pharmacokinetic studies in healthy volunteers have suggested that single doses up to 120 mg of ivermectin can be safe and well tolerated.13 However, even with this dose, which is 10-fold greater than those approved by the US Food and Drug Administration, the Cmax values reported were ∼250 ng/mL,13 one order of magnitude lower than effective in vitro concentrations against SARS-CoV-2.

  28. So 7-day average in infections in Sweden is up to 809 from 170. Is there any theoretical point where Nic’s assertion of reaching a herd immunity threshold, months ago, is falsified?

    • There are so many unknowns. Those are actually detected infections, not all infections known and unknown.

      • So many unknowns, yes,and yet people declared thst Sweden reached a “herd immunity threshold” dice months ago.

        Respect the uncertainties.

    • Yep. Falsified. It’s toast.

      Actually infections are likely a lot more.

    • As for “detected” infections resulting from testing, wastewater testing indicates an increase in spread recently, also. That’s independent of testing.

      • And from that same study, ICU populations are still down. This rise could be school children going back to school?

        https://www.kth.se/aktuellt/nyheter/avloppsvatten-visar-stor-okning-av-covid-19-i-stockholm-1.1016275

      • > This rise could be school children going back to school?

        Seems to some degree likely. In comparison to Finland it looks like they’ve had more school-based outbreaks.

        But one of the reasons why Sweden shouldn’t be used as an example for other countries like the US is that its probably much easier for Sweden to isolate older people from infected school children (extensive social safety net that helps to provide caregiving alternatives for vulnerable caregivers, low % of multi-generational households, easier for people to work from home – meaning people who do get infected by children in their household are less likely to contribute to community spread), etc.

    • Herd immunity has not yet been reached in Sweden. their policy to minimize impact on their economy made sense

      • Sweden was rather uniquely situated to employ such a strategy. A public that conforms to directives (they reduced activity at similar levels to neighbors), very high % of single-individual households, high standard of living and good baseline health (and low % of comorbidities), high % of people who could work from home, extensive social safety net (funded by extremely high taxes), low % of multi-generational households (and thus low % of primary-caregiver grandparents, etc.

        And yet thwy had many, many more deaths and illness per capita than the most comparable countries. With as if yet, little of any relative economic gain raealized. That might change over time but they don’t appear to be significantly more open at this point than other Nordic countries.

        And meanwhile, depending on the trajectory of a vaccine distribution – they will never equalize pwr capita rates of death and illness even if they have reached “herd immunity.” earlier than other countries.

        But keep putting gi has in the sand and looking at the issue from one side only.

      • We may be looking at the Sweden response through a US societal lens. Euthanasia is legal in Sweden. They may have considered the deaths of the susceptible vs the overall health of the economy and the well-being of the balance of citizens.

      • At what rate do you think herd immunity be reached?

        If hospitals are not being overwhelmed in any particular area why shut down the economy?

      • > Euthanasia is legal in Sweden. They may have considered the deaths of the susceptible vs the overall health of the economy and the well-being of the balance of citizens.

        They only gave limited care (e.g., didn’t even give oxygen) to infected older people in elder care housing – didn’t transport to hospital (to prevent spread). No way that flies here with the conservative (“death panels!!!”) block who are so in love today with SOSHLIST Sweden and “rationing healthcare!!!’

      • Joshua

        I didn’t write that all of Sweden’s policies were perfect.

        You ignore what I asked.

        If the US hospital system in any particular area is not being overwhelmed, why have shutdowns

      • Rob Starkey: If the US hospital system in any particular area is not being overwhelmed, why have shutdowns [?]

      • First, there was significant economic impact in Sweden despite their policies.

        Second, nobody at the moment is advocating shutting down the entire economy nor is that policy being pursued anywhere. If anything in the US, we are following almost the same policy as Sweden. Some reasonable mask wearing requirements and crowd size control is not the same as shutting down the entire economy.

  29. In a small study in San Francisco, Abbott’s BinaxNOW identified infectious people nearly as accurately as a P.C.R. test.

  30. JAMA on excess deaths in 2020, March through August:

    https://jamanetwork.com/journals/jama/fullarticle/2771761?guestAccessKey=3e8d8f2f-d583-44a3-9d53-8b0f57e49df2&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jama&utm_content=etoc&utm_term=102020

    snippet: Of the 225 530 excess deaths, 150 541 (67%) were attributed to COVID-19. Joinpoint analyses revealed an increase in deaths attributed to causes other than COVID-19, with 2 reaching statistical significance. US mortality rates for heart disease increased between weeks ending March 21 and April 11 (APC, 5.1 [95% CI, 0.2-10.2]), driven by the spring surge in COVID-19 cases. Mortality rates for Alzheimer disease/dementia increased twice, between weeks ending March 21 and April 11 (APC, 7.3 [95% CI, 2.9-11.8]) and between weeks ending June 6 and July 25 (APC, 1.5 [95% CI, 0.8-2.3]), the latter coinciding with the summer surge in sunbelt states.

    • Covid-19 deaths no longer correlate with infection but treatment and quality of care. Modulated Dexamethasone administration is attributed to reducing mortality by 30% alone. Antivirals including HQZ, Ivermectin and others as well as Vit D supplementation are reducing severity. Like AIDS, soon enough, no one need die from a SARS2 infection except in the case of extreme comorbidity.

      Covid-19 is an immune pathology that involves the central nervous system with symptoms that may not present well after the initial infection has cleared.

      Our highest priority is stopping the spread of the virus. For too long the epidemiologists have controlled the narrative. It is time we heard from hematology, endocrinology, pathology, gastroenterology and the immunologists. (This is a statement on the compartmentalization of medical research.) If the pubic understood the long term risk of infection articles such as this WUWT would be recognized as irresponsible..

      • Hmm. I’m not sure why you think the article was irresponsible – my take away is that it would be in broad agreement with the rest of your comment. I found both your comment and the article interesting.

    • I consider rationale for rolling back public health measures based on decreasing deaths irresponsible. Deaths decrease with clinical successes.
      Protective Immunity must not be confused with sterilizing immunity: The infected who may not know they are infected are infectious.

      I see the that the Woolf et.al. article on excess deaths published in JAMA is linked here and would support keeping public health measures in place.

  31. 7-day average of infections in Sweden up over 600% during the last 6 weeks.

    Is there any point at which the conclusion, based on theoretical modeling (that failed to account for many uncertainties and confounding variables, btw), that Sweden reached “herd immunity” months ago is falsified? If so, what would be the metric that would falsify it?

    Inquiring minds want to know.

  32. Case rate up 700% in Sweden. Doubled in NYC, reaching a level not seen since the end of May.

    At what point does Nic become conspicuous by his absence?

    • Joe - the non epidemiologist

      Josh – case rate up in Sweden by 700%

      So what ?
      daily death rate still in 1 to 3 per day, except yesterday with 7. Basically exactly what you want to happen. A lot of increase in immunity with virtually zero death

      • > So what ?

        1) The immidate question at hand is Nic’s declaration thst Sweden reached “herd immunity” 5 months ago

        2) illness occurs w/o death.

        3) it’s not clear that after accounting for lags, deaths won’t increase.

        4) related to #3, if the focus is on “protecting the vulnerable,” more infected people makes thst more difficult.

        5) Sweden is uniquely situated to minimize deaths resulting from infections as compared to countries such as the US. As such, Sweden shooting up in their infection rate should serve as a cautionary example for Americans looking to Sweden and touting “herd iinity” as a model we should follow.

        6) (at least in the US) with increases in cases comes increases in hospitalizations which means more pressure on frontline Healthcare workers. You may think “so what” in response to that. I don’t.

        7) with increased infections comes more fear of infection – particularly for the most vulnerable populations. That puts stress on people in a variety of ways. For example, they might be less likely to seek needed medical care. It might make them more likely to isolate, with deliterious effects.

        8) easy for you to say “so what.” A grandparent who is a primary caregiver for their grandchild might not be as cavalier about increases in infections as you are.

      • Sweden’s infection rate really started taking off about 6 weeks ago.

        We are starting to see a rise in death rates here just about 6 weeks after the infection rate started rising again. I don’t know about the lag time in Sweden but that has been pretty consistently the time lag between increases in infections and increases in deaths here in the US.

        I guess since you said “So what” you must know that the lag time in Sweden is shorter than 6 weeks and thus there’s no reason for concern. Would you mind providing a link to your source on that?

      • Joe - the non epidemiologist

        Josh – the 7 day moving average for deaths in sweden as of Oct 24, oct 25 is 1. The 7 day moving average over the entire month of Oct got no higher than 4. The 7 day moving average death rate never got above 3 in august or september.

        The uptick in cases began in mid August and continued into sept and oct. Taking into account the 4-6 week lag time, the surge in deaths isnt matching the surge in cases.

        The 700% increase in the infection rate is a good thing. it means the immunity is continuing to spread without the surge in deaths or serious illness.

        https://www.worldometers.info/coronavirus/country/sweden/

        Out of the 8 reasons you stated – only #7 explains your reasoning – “fear”

  33. CDC finally updated the Covid 19 hospitalization weekly numbers for 10/17. Hospitalizations are way down. These laboratory confirmed numbers are subject to revision.

    https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

    • > The overall cumulative COVID-19-associated hospitalization rate through the week ending October 17, 2020 was 193.7 hospitalizations per 100,000 population.
      Since the week ending September 26 (MMWR week 39), weekly hospitalization rates have increased for all age groups combined, driven primarily by an increase in rates among adults aged 50 years and older. Data for the most recent weeks may change as additional admissions occurring during those weeks are reported.

      https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html#:~:text=The%20overall%20cumulative%20COVID-19,193.7%20hospitalizations%20per%20100%2C000%20population.

    • Joshua is looking at data that uses “indicators” to determine a Covid 19 infection. The chart to which I supplied a link uses laboratory confirmed data. 5.1/100,000 for week ending 10/10 and 3.4/100,000 for week ending 10/17. Josh is quoting a cumulative rate (which isn’t really what I would call a rate, since rates are judge on equal time periods) , not the weekly rate.

      The text Josh quoted is from the CDC web site, but does not comport with their own charts.

      • Jim –

        > Josh is quoting a cumulative rate (which isn’t really what I would call a rate, since rates are judge on equal time periods) , not the weekly rate.

        Here’s a suggestion – in a contest between the World’s top experts in epidemiological surveillance at the CDC, and some conspiracy-minded dude with a wifi connection, if there’s a discrepancy you might want to consider that it’s the dude who made an error and not the CDC scientists. Not to say that the dude can’t possibly be right and the CDC experts wrong… but maybe the dude being wrong should generally be the default choice?

        -snip-

        The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) conducts population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations in select counties participating in the Emerging Infections Program (EIP) and the Influenza Hospitalization Surveillance Project (IHSP).

        A total of 63,152 laboratory-confirmed COVID-19-associated hospitalizations were reported by sites between March 1, 2020, and October 17, 2020.

        *****The overall cumulative hospitalization rate was 193.7 per 100,000 population.*******

        Overall weekly hospitalization rates among all ages combined first peaked during the week ending April 18 (MMWR week 16), followed by a second peak during the week ending July 18 (MMWR week 29). Since the week ending September 26 (MMWR week 39), overall weekly hospitalization rates have increased for all ages combined, driven primarily by an increase in rates among adults aged 50 years and older. Data for the most recent weeks may change as additional admissions occurring during those weeks are reported.

        -snip-

      • Notice the trend. Then notice the date. Think:

        https://gis.cdc.gov/grasp/covidnet/COVID19_5.html

  34. Nic: Sorry I’m so late in asking questions about this post. Question #1: The passage below is from your reference #3 (Tkachenko)

    “Following in the footsteps of Refs.(12, 13, 15, 18, 26, 28), we consider the spread of an epidemic in a population of individuals who exhibit significant heterogeneity in their susceptibilities to infection α. This heterogeneity may be biological or social in origin, and we assume these factors are independent: α = α_b*α_s . The biologically-driven heterogeneous susceptibility α_b is shaped by variations of several intrinsic factors such as the strength of individuals’ immune responses, age, or genetics. In contrast, the socially-driven heterogeneous susceptibility α_s is shaped by extrinsic factors, such as differences in individuals’ social interaction patterns (their degree in the network of social interactions). Furthermore, individuals’ different risk perceptions and attitudes towards social distancing may further amplify variations in socially-driven susceptibility heterogeneity. We only focus on susceptibility that is a persistent property of an individual. For example, people who have elevated occupational hazards, such as healthcare workers, typically have higher, steady values of α_s. Similarly, people with low immune response, highly social individuals (hubs in social networks), or scofflaws would all be characterized by above-average overall susceptibility α.

    In this work, we group individuals into sub-populations with similar values of α and describe the heterogeneity of the overall population by the probability density function (pdf) of this parameter, f(α). Since α is a relative measure of individual susceptibilities, without loss of generality we set ⟨α⟩ ≡ Integral from 0 to infinity of αf(α)dα = 1. Each person is also assigned an individual reproduction number Ri, which is an expected number of people that this person would infect in a fully susceptible population with ⟨α⟩ = 1. Accordingly, from each sub-population with susceptibility α there is a respective mean reproductive number Rα. Any correlations between individual susceptibility and infectivity will significantly impact the epidemic dynamics. Such correlations are an integral part of most network-based epidemiological models due to the assumed reciprocity in underlying social interactions, which leads to Rα ∼ α (10, 18). In reality, not all transmissions involve face-to-face contacts, and biological susceptibility need not be strongly correlated with infectivity. Therefore, it is reasonable to expect only a partial correlation between α and Rα.”

    Do I correctly understand that this model and others like it assume that the “socially-driven heterogeneous susceptibility α_s” remains constant for each subpopulation throughout the pandemic? In other word, a socially gregarious person’s susceptibility to infection will remain the same throughout the pandemic and will not be reduced by: wearing a mask, or adoption of social distancing practices, or fear that they might become infected (if personally vulnerable or a family member is vulnerable). If so, it is insane to apply such a model to a real pandemic and derive parameters from observations. It seems obvious to me that the behavior of real people changes during a pandemic. The slowdown in exponential growth in the US pandemic this spring occurred with 7 to 17 days after lockdowns were begun. Attributing that change to approaching herd immunity will grossly over-estimate the importance of heterogeneity in susceptibility in approaching HIT causing new cases to plateau and fall. Cumulative confirmed cases in the Dakota’s today are 4.3-4.8% of the population (4839 and 4311 per 100,000) but New York, the heart of the early pandemic in the US, now has mid-range cumulative confirmed cases totaling 2.5%.

    The weakness in my argument is that I don’t know how increasing availability of testing has changed the ratio of detect:silent:total infections. Early in the pandemic (May?), combined serology studies suggested that there were about 10 silent infections for every confirmed infection. If I applied that ratio to North Dakota today, nearly 50% of the population has been infected and that number is still rising. Question #2. Does anyone think the 10:1 ratio is still valid today? In models, I see assumptions that half of infections are asymptomatic.

    Minnehaha County, South Dakota with 185,000 or 200,000 residents living in Sioux Falls, has just over 10,000 confirmed infections (5% or 5000/100,000) and has experienced a sizable spring and fall surge in cases. As best I can tell, it is an extremely attractive location in the US to look for approaching herd immunity.

    You’ve argued that deaths are more reliable than confirmed cases. Cumulative deaths in Sioux City are 54/100,000 about 1% of confirmed cases, and 1-2/100,000 per day. By way of comparison, NYC has experienced 3,100 cumulative cases per 1000 (3.1%), but 284 cumulative deaths/100,000 (.28%), almost 10% of the number of confirmed cases – and nearly 10-fold more than Sioux Falls. Why? Did we miss 10 times as many cases in NYC in April as in Sioux Falls due to limited testing. The nationwide positivity test rate has only fallen 2-fold since April. Did the pandemic get into nursing homes before they could be protected? Not likely, NY’s nursing home death rate is about average at 5%, with 15% testing positive. In SD, 2% of nursing home residents have died and 10% have tested positive. The odds of going home after hospitalization have doubled, but younger patients are being hospitalized.

    I clearly have no idea of what is going on. Does anyone have a reliable big picture?

    • Frank
      I agree that changes in people’s behaviour, whether mandated or voluntary, over the course of the epidemic are a likely confounding factor in estimating its key parameters, including the degrees of heterogeneity in biological susceptibility and in social connectedness, from the dynamics of the epidemic. So may be other factors such as seasonal influences and the extent of continuing seeding from outside the area under study.

      IMO it is safer to judge when herd immunity has been reached from evidence indicating that new infections have peaked. But the HIT is a function of R0 and of the degrees of heterogeneity in biological susceptibility and in social connectedness, the first and third of which are affected by people’s behaviour, seasonal influences, etc. If people return to normal behaviour after infections have declined to low level, the HIT will then be higher, and infections may start to rise again, albeit more slowly than oroginally. This seems to me one likely reason for the second wave in Europe. Lockdowns may have aggravated the second wave by preventing a strong first wave developing outside one or more cities or regions.

      Much published case data is of little use for properly judging the number of new infections. In England, the public health authority has aparently even (re)started multiple counting positive cases when calculating the positive test percentage!

  35. Here is a more “vital” statistic than covid hospitalizations. Death by CV
    19 has been steadily trending down. This is more meaningful that cases, for sure.

    Week of: CV Deaths All Deaths
    9/26/2020 3,669 53,968
    10/3/2020 3,309 50,719
    10/10/2020 2,889 45,122
    10/17/2020 1,035 25,660

    https://www.cdc.gov/nchs/nvss/vsrr/COVID19/index.htm

    • You really don’t learn, do you?

      Death rates will likely follow the trend of hospitalizations (although not in direct proportion as treaents get better) with a lag. Hospitalizations are trending up. Those data you showed don’t allow for the lag between hospitalizations and deaths.

      Why is deaths a more “vital” than hospitalizations? Hospitalizations means that someone is seriously ill. Many of those hospitalized but who don’t die will be those who had a better baseline health, are younger, etc. Hospitalizations from COVID have significant societal impact.

      • From the CDC…

        -snip-

        The percentage of deaths due to PIC have been declining since late July; however, in mid-September the percentage leveled off. Data for the most recent weeks currently show a decline, but that is likely to change as additional death certificates are processed.

        -snip-

      • What you have failed to learn, Joahua, is what our health professionals have learned and continue to learn. They know much better how to treat CV19. A cheap steroid is saving lives and I’m sure other therapeutics and therapies will be discovered. And this doesn’t include potential compassionate use of the modern ones like the Regeneron antibody cocktail. CV19 isn’t “nothing” but the improving situation is masked by the constant drumbeat of simple cases by the Trump-hating press.

      • Jim –

        There is no doubt that treatments have improved. It is likely that further improvements are to come.

        That said, all across Europe hospitalization rates and death rates have increased with a lag as infections have increased. The same pattern has applied here. The last time infections spiked, Trump apologists said it was only an artifact of more testing and younger people getting infected. They were wrong and the increase in hospitalizations and deaths followed. Now we have recently seen increased infections and with the corresponding lag, hospitalizations have started to increase accordingly.. Death rates have just started to tick up (by some 15%) as well and there is good reason to expect that further increases in death rates will follow. I hope it doesn’t happen, but even with improvements it would be foolish to think that deaths rates won’t continue to rise unless there is solid evidence to suggest otherwise. You keep referencing evidence without accounting for the appropriate lags and expecting the pattern to just magically disappear. You’re entitled but it’s likely to prove in error.

        The CDC says that we have already seen more hospitalizations, that we should expect that trend to continue. It only stands to reason that there will be an increase in deaths as well.

        The problem in this country relative to European countries, is that our baseline death rate is is much higher than theirs were. Recently in many countries in Europe, death rates have increased more than 10 X after a lag since their infection rates increased. But their baseline death rates were very, very low compared to ours. Some have gone from less than 10 deaths per day to well over 100 deaths per day. But here we’d be facing increases in death rates moving up from 500 per day or more at baseline. Even if we go up only something like 5 X rather than the 10+ X increases seen all over Europe, we’re in big trouble.

        I think the CDC has aa better handle on the situation than you do and I think the chances are much greater that they are right and you are wrong. But I certainly hope you’re right.

      • jack smith – given all the note-worthy situations we face, I’m thinking “Santa-gate” won’t get off the ground.

      • Joshua wrote: “That said, all across Europe hospitalization rates and death rates have increased with a lag as infections have increased.”

        I think not. Have you looked at data for Sweden?

      • Nic

        Sweden’s most recent data seems to show that hospitalizations have risen although the death rate seems fairly flat.
        The total harm to the country seems less by their approach even though there were mistakes.

      • Actually, I meant Western Europe.

        Thus far, Sweden, Norway, Finland, and Denmark are all exceptions to the pattern. All have seen large spikes in infections but not noticeable spikes in deaths.

        One more uncertainty. It’s early times. We should all resist the tendency to “over fit.”

      • It would be useful to see a break down in positivity rates stratified by age in Europe and Scandinavia. Here, the CDC is reporting an increase across all age groups. Don’t know about Western Europe. That could theoretically be a differentiator. The Nordic countries are very well set up, relative to Western Europe and even more so than the US, to protect vulnerable people for a variety of reasons.

      • OK –

        I found this:

        Also this:

        And this:

      • And this:

      • -snip-

        UPPSALA, Sweden — Welcome to local lockdown, Swedish style.

        Uppsala, a city of 230,000 people about an hour’s drive north of Stockholm, on Tuesday became the first place in Sweden to announce tougher localized guidance aimed at slowing a spike in cases of COVID-19, which authorities say has put hospitals there under pressure.

        Residents were told to avoid public transport and not to socialize with anyone they don’t live with.

        -snip-

        https://www.politico.eu/article/sweden-coronavirus-local-lockdown-uppsala/

      • “Back to the topic of lag between cases and hospitalizations, or between cases and deaths.

        In Sweden the lag also appears to be 5 weeks, as ICU admissions and deaths have just now started increasing:https://t.co/femhvSdiG6

        A 5 week delay from positive test to ICU admissions? In your dreams, Josh. You seem to believe everything that supports your – I presume authoritarian – beliefs.

        ICU admissions in Sweden were 16 in the last week (data to 22 Oct). They were 18 in the previous week, and 15 in the week before that. It doesn’t really support your “have just now started increasing” statement, does it?

        It’s true that ICU admissions were even lower from mid-August to late September, but under 20 a week is still a tiny figure for a population of over 10 million.

        Much the same pattern, a week or so delayed, exists for Swedish deaths recorded as COVID-19 linked.

        Why don’t you try examining source data yourself? Too busy making comments, maybe.

      • Nic –

        > In your dreams, Josh. You seem to believe everything that supports your – I presume authoritarian – beliefs.

        Apparently you attributed the comments of someone else to me?

        I post information that supports different conclusions, knowing that there are a lot of uncertainties even if people think they’ve figured this stuff out. For example, I was wondering about the stratification about age in infections and posted a link that shows infections mostly among younger people. That said, I have noted many times that you have a very selective approach to the uncertainties so your accusation is a bit rich.

        There was some ambiguity in the comments (of someone else) that I posted, with respect to conflating lag times in ICU admissions and deaths, but I’ll note that he did say ….

        > “Same 5-week lag for *deaths*”

        After referencing a 5-week lag to *deaths *in other locations and saying it was the *same* in Sweden.

        Perhaps you’ll want to a comment on his Twitter feed to get him to clarify? I have no idea where he’s getting his data.

        I’ll also note that you seem to dismiss any uncertainties with respect to lags in the reporting and recording of ICU admissions. Maybe there is none, but Sweden’s system for reporting on the stats on infections seems a bit uneven from what I can tell.

      • You did realize that you were quoting someone else there, not me – right?

      • Joe - the non epidemiologist

        Josh – The 7 day moving average daily death rate in sweden is sitting at 1.

        700% increase in the infection rate – but no increase in death rate

        High infection rate means immunity is spreading quickly.

        Current Death rate much lower than the seasonal flu

      • Deaths are no longer a relevant metric. Like AIDS, no one need die from SARS2 infection. Clinicians are getting a handle on the pathology and are intervening successfully.

        How will we provide for these people.
        https://news.sky.com/story/long-covid-the-debilitating-after-effects-of-coronavirus-12104961

        Herd immunity is off the table for those familiar with the pathology.

      • Let’s hope it stays that way…

        Still a bit early to tell if it will be sustained given the lags involved.

        Deaths is not the only relevant metric.

        The question at hand is the status of “herd immunity,” where infections is entirely relevant.

        Sweden doesn’t stand out in the respect that you are pointing to compared to the other Nordic countries with similarly high increases in infections with no significant increases in deaths. So the notion that Sweden is significantly more advanced towards “herd immunity” comes into question.

        This has all happened after Sweden has experienced massively more deaths and illnesses compared to the most similar countries.

        That doesn’t mean that I would think that Swedes don’t have the right o determine what policy is best for themselves. The point that I make is w/r/t trying to extrapolate from Sweden to infer which policies we should be following.

        This has all been pointed out to you previously.

      • -snip-

        A total of 55 people were being treated for Covid-19 in intensive care on Monday – or 15 percent of all patients in intensive care, according to the latest official figures.

        “We’re starting to approach a critical point here in Sweden as well,” said Tegnell.

        The number of intensive care patients is still low compared to spring, when more than 500 Covid-19 patients were on ventilators at the peak, but it has doubled in the past week and the majority of Sweden’s regions expect the current situation to deteriorate.

        -snip-

        https://www.thelocal.se/20201027/sweden-nears-critical-point-as-coronavirus-cases-surge

      • Josh

        I understood you to be quoting the 5-week lag comment approvingly.

        “I’ll also note that you seem to dismiss any uncertainties with respect to lags in the reporting and recording of ICU admissions.”

        Why not check the position for yourself before making such a comment?
        My understanding is that the Swedish ICU reporting system is real-time, so there is no lag (or, at most, one day).

        There is certainly considerable uncertainty in the lag between symptoms appearing and death, and both the mean and the shape of the lag distribution vary between countries and, no doubt age groups. It probably also changes over time, as treatments improve and countries such as Sweden and the UK that limited ICU admissions of very old people in the spring may now be doing so to a lesser extent or not at all.

      • Nic –

        > I understood you to be quoting the 5-week lag comment approvingly.

        “Approvingly” is an odd term.

        Am I approving or not approving of what Tegnell is saying here? Neither.

        -snip-
        “We’re beginning to approach the ceiling for what the healthcare system can handle. Together, as during the spring, we can push down this curve and avoid the strain on healthcare,” Chief Epidemiologist Anders Tegnell told a news conference.

        The Health Agency also moved to tighten pandemic recommendations for three additional regions, including Sweden’s biggest cities Stockholm and Gothenburg, saying infection rates were rising sharply in these areas.

        Sweden has relied primarily on voluntary measures, largely uninforced but still widely adhered to. The new tighter local recommendations, already introduced in two regions with surging infections, included advice to avoid indoor environments such as shops and gyms.

        Stockholm authorities said separately that the number of Covid-19 patients in need of care in the region had risen about 60% over the past week after a near 80% surge in recorded infections.

        -snip-

        https://www.thelocal.se/20200414/understanding-swedens-figures-on-the-coronavirus

        > My understanding is that the Swedish ICU reporting system is real-time, so there is no lag (or, at most, one day).

        -snip-

        The agency says on its website: “The number of reported cases is constantly changing as people seek care and are examined for the virus.

        “There is some delay in reporting and supplementing data on new cases and deaths, so the numbers from recent days (especially during weekends) should be interpreted with caution. The statistics are compiled daily based on reports received up until 11.30am the same day. The current and previous day’s number is incomplete and will only be complete the following day.”

        -snip-

        Maybe close to real time if it’s not on a weekend or near a holiday, but I’d say it’s unrealistic to think that there aren’t other factors causing delays or lags – especially when hospitals are over-taxed as they are becoming now, or if the dats is coming from more rural regions. They just made an adjustment to the number of deaths (dropping it by 15), for example.

        But regardless it’s just a bad practice to make *assumptions* in real time. You keep making that mistake. You did it when the infection #’s first dropped (concluding that they proved achieving a “herd immunity” status). You did it when they first started going up again (highlighting/assuming it was only among younger people – and not even taking into account that when more young people get infected, over time that will mean that more older people will get infected as well unless older people can be sealed off perfectly), you’ve done it with ICU admissions and deaths (pointing to them at a fixed point early on and suggesting that was some kind of an indication of a changed state of play that would allow for extending the theory of “herd immjnity” as if there wasn’t uncertainty as to whether they’d increase over time).

        > There is certainly considerable uncertainty in the lag between symptoms appearing and death, and both the mean and the shape of the lag distribution vary between countries and, no doubt age groups. It probably also changes over time, as treatments improve and countries such as Sweden and the UK that limited ICU admissions of very old people in the spring may now be doing so to a lesser extent or not at all.

        So again we see that you leverage the uncertainties with a directional focus – with a suggestion of an exit ramp where you can maintain your assertion of “herd immunity” status (5 months ago) and say that a recent increase in ICU admissions in Sweden might just be because they’re admitting a higher % of infected older people rather than because more older people are getting seriously ill once again.

      • Re: (Nic Lewis) “In your dreams, Josh. You seem to believe everything that supports your – I presume authoritarian – beliefs.”

        “[A]uthoritarian”, eh? Sure…

        “Sweden’s upper secondary schools are again closing their doors to students from Monday until after Christmas.
        […]
        They said it was “necessary” in order to curb a resurgence of the coronavirus across Sweden.”

        https://www.thelocal.se/20201203/swedens-schools-for-over-16s-shift-back-to-remote-learning

        “Sweden on Monday announced a ban on public events of more than eight people at a press conference where ministers urged the population to “do the right thing”.
        […]
        The new limit is part of the Public Order Act and therefore is a law, not a recommendation like many of Sweden’s coronavirus measures. People who violate the ban by organising larger events could face fines or even imprisonment of up to six months.”

        https://swedishchamber.nl/news/sweden-bans-public-events-of-more-than-eight-people/

      • Re: (Nic Lewis) “[from Joshua: “Back to the topic of lag between cases and hospitalizations, or between cases and deaths.
        In Sweden the lag also appears to be 5 weeks, as ICU admissions and deaths have just now started increasing:https://t.co/femhvSdiG6”%5D
        A 5 week delay from positive test to ICU admissions? In your dreams, Josh. You seem to believe everything that supports your – I presume authoritarian – beliefs.”

        https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-930346

        https://web.archive.org/web/20201210011949/https://www.dn.se/sthlm/99-procent-av-iva-platserna-i-stockholms-lan-fyllda-laget-ar-mycket-allvarligt/

    • jim2,
      Give me your honest opinion of how trustworthy the CDC is under Trump.
      https://www.wsj.com/articles/health-agency-scraps-coronavirus-ad-campaign-leaving-santa-claus-in-the-cold-11603630802?mod=djemalertNEWS

      How low can you go to bribe and coerce Santa Clause to brainwash the little children with your “herd immunity” BS.

      • And that was a plan to promote a vaccine, not herd immunity, Jack.

      • The idea of vaccinating Santa Clauses came from Michael Caputo, a political operative Trump posted in HSS to get better publicity during the pandemic. The CDC had nothing to do with it. The CDC knows that a vaccine will likely not be ready in time, will not provide those vaccinated with protection for several weeks and that we don’t know what fraction of those vaccinated will be protected.

        The lowest acceptable protection percentage is 50%. If 70% of the country were vaccinated with 50% protection, that alone would get us to halfway to the traditional threshold for herd immunity. Same for 50% of the country (the percentage getting flu shots) and a vaccine that protects 70%. Either would be a game-changer even if traditional estimates of 70% and 70% might end the US pandemic quickly.

        However, putting Santa’s with anything less than 99+% protection in contact if hundreds of people per day would be insanity in the middle of a pandemic.

      • Franktoo,
        Yeah I know the difference between HHS (Azar) and CDC (Redfield) and that was wrong. The entire family of public health institutions HHS/CDC/FDA/EPA are politically corrupt so forgive me if I mixed up the acronym. Each one has a rap sheet as long as your arm from all the criminal malfeasance that has gone unpunished.

  36. I asked my doctor if he thought hydroxychloroquine could help cure CV19. I was somewhat surprised when he said yes. But what he said next illustrates the travesty of the CV19 therapeutic situation. He said they will administer it only once the patient is in the hospital. If you are diagnosed with CV19 and have mild symptoms you are sent home to self-quarantine. But you are sent home without hydroxychloroquine with or without azithromycin.

    The best was to treat CV19 is early. The earlier it is treated, the better chance your immune system has to develop the antibodies needed to kill it off. Sending people home without therapeutics is malpractice and cause partly by the loony-left press, Dimowits, and other with TDS. Blood is on their hands.

    • Jim2: Unfortunately, studies in the laboratory show that HCQ doesn’t appreciably slow down the growth of CV19 in mammalian cell culture experiments at the concentrations it is found in the blood after dosing. So, unless some mechanism magically concentrates HCQ exactly where it is needed, it won’t help patients with CV19. Other drugs used for treating flu, HIV, HCV, etc produce blood levels well above the concentration that inhibits viral replication in cell culture experiments.

      Clinical trials show HCQ has no benefit when patients are randomly assigned to get HCQ or no HCQ. Other studies where doctors choose who gets HCQ and who doesn’t are problematic. Do you given HCQ to an older patient with cardiovascular problems who might died from HCQ induce arrhythmia? If not, the no HCQ group would be more likely to die even the HCQ had been replaced by a placebo.

      Azithromycin has no effect on CV19 replication in cell culture, but it is good for treating pneumonia, which some CV19 patients eventually develop. But there is no need to administer it until pneumonia is detected.

      Remdesivir does stop viral replication in cell culture experiments at concentrations well below those observed in the blood stream. It could be given to prevent a patient from getting seriously sick. Unfortunately, it can’t be given orally and is normally administered by IV. This is exactly what Trump’s doctors did for him, but they gave him Regeneron’s synthetic antibodies too – which are currently undergoing clinic trials.

      Jim2 writes: “The best was to treat CV19 is early. The earlier it is treated, the better chance your immune system has to develop the antibodies needed to kill it off. Sending people home without therapeutics is malpractice …”

      … only if you have no safe and effective drug to send them home. One or both of the treatments President Trump received did a fantastic job of keeping Trump from getting desperately ill and helped him recover quickly.Note that Trump’s doctors didn’t give him HCQ when he definitely had CV19. Unlike President Trump, who got test results almost immediately, it may take two days or longer for the average person to get back a positive PCR test and begin treatment. And we don’t have the hospital space to provide IV treatments for everyone for CV19 before the get seriously and perhaps life-threateningly ill. Nor before they exhibit symptoms or need hospitalization.

      Now, if you were a doctor who believed that HCQ MIGHT offer your exposed patient SOME benefit while waiting to see if he would come down with COVID, you are allowed to prescribe it. But first, that doctor should ask himself: “What are the chances my patient (30 or 40 or 50 or 60 or 70 or 80 year old) will die of COVID. Family member have a less than 50% chance of transmitting CV19 to each other and other contacts are significantly less risky. In Taiwan, where they have mandatory quarantine for all contacts, about 1% of ordinary contacts result in transmission. So your 80 year old patient may have as little as 1% chance of getting COVID on top of his 30% chance of dying if contracting it or 0.3% combined chance of dying. What are the chances that HCQ will kill that 80-year-old by QT prolongation, torsade de pointes, or arrhythmias? No one knows, but it happens sometimes and 14 other drugs have been removed from the market for causing QT prolongation. If your patient has an ECG, you can weed out those most at risk, but you are talking about treating a non-hospitalized patient. With younger and younger patients the cardiovascular risk of administering HCQ drops rapidly AND so does the risk of dying from COVID.

      In this country, a licensed physician can prescribe any approved drug he thinks might help his patient, even if it wasn’t approved to treat that patient’s condition. If a doctor thought HCQ actually helped prevent COVID, a doctor might prescribe HCQ to a patient who contacted someone with COVID. He’s betting his patient has a greater chance of dying from COVID than from HCQ. (Trump’s doctor monitored Trump’s heart multiple times a day when he was on HCQ and he had a recent ECG, but your average patient at home won’t be monitored at all.) But most doctors aren’t willing to take that risk when there is now good evidence HCQ doesn’t help COVID patients.

      This is why you are wrong to accuse most doctors of malpractice. All drugs have some side effects, some of them deadly. In those cases, you need to be sure your patient is more likely to be saved by your treatment than killed by it. Drug companies spend hundreds of millions testing their drugs and vaccines, sometimes in more than 10,000 people. That allows them to clearly characterize how efficacious drugs are and detect rare side effects that might kill people. So far, 200,000 Americans have died of COVID, approaching 0.1%. How many people might die of allergic shock from a COVID vaccination? It better be much less than 0.1%, or you might kill more American with your vaccine than you save from COVID.

      • Frank – Thanks for your opinion. But like I said, I asked my DOCTOR. He is a DOCTOR, my doctor. He has served me well lo these many years and I believe him.

      • Jim2: I’m glad you have faith in your doctor. Did you ask if he personally read the papers on clinical trial with HCQ? Does he know if a particular study was random-assignment?

        The truth is that many doctors, especially GP’s, learn about medicines in medical school and rarely read papers about new medicines, especially medicines that treat conditions the doctor rarely encounters. Doctors are overwhelmed with things they need to do to take care of their patients and reading the new literature rarely rises to the top of that list. That’s why we have specialists; many of them read papers about new drugs in their field of specialty. However, once out of medical school, many doctors are educated by sales representative from pharmaceutical companies or at meetings sponsored by drug companies where they hear talks by experts in a new medicine. If the sales rep hasn’t been by to see your doctor and drop off free samples of a new medicine and some literature, their company probably isn’t selling a new product that your doctor needs to know about. In many cases, educating your doctor about a new drug can consume about half of the cost you pay for that drug. Sorry to sound so cynical.

        Unfortunately, sales reps don’t come around with new information about old drugs that are off-patent, like HCQ. If you doctors isn’t treating COVID patients in a hospital, he probably doesn’t have time to keep up with the flood of papers about treating this condition.

      • Frank – you don’t know my doctor. You are shooting in the dark. Give it up.

  37. For the edification of those here who have stated with confidence that the season flu is deadlier for young people than Covid:

    • Seems a rather odd development, given that they reached “herd immunity threshold” status 5+ months ago.

  38. Looks like some if not many of the Swedes have adopted good practices without a fiat from Big Brother. Even countries with government mandated lockdowns have spikes.

    And while images in the media occasionally show crowded city buses and restaurants, surveys by the Swedish Civil Contingencies Agency found that 80 percent of Swedes have changed their behaviour as a result of recommendations.

    They are working from home or limiting social contacts — even though there are no fines or sanctions for disregarding them.

    https://news.yahoo.com/sweden-sticks-guns-covid-cases-072952206.html

  39. New COVID-19 deaths remain low and Sweden’s official death toll had decreased by 15 cases since Friday, taking the total to 5,918 deaths.

    https://www.yahoo.com/news/sweden-registered-1-870-covid-134159924.html

  40. -snip-

    People who have had close contact with people with confirmed COVID-19 infections who took hydroxychloroquine were just as likely to get COVID-19 as were those who received a placebo, according to a preliminary data analysis from a large randomized, controlled trial. Researchers at the University of Washington School of Medicine in Seattle led the study.

    -snip-

    https://newsroom.uw.edu/news/hydroxychloroquine-fails-prevent-covid-19

  41. A lot is being made of what was pointedly described as a “toy model.” This sort of exaggeration of the import is typical behavior of the looney left. Whomever they deem to be the enemy, they point to any shortcoming real, or (frequently) imagined, or (very often) made up out of whole cloth. Plausible deniability seems to be the watchword of the day for our socialist/left-wing-nut friends.

  42. Joe - the non epidemiologist

    interesting article showing significant correlation of the current surge in Europe with latitude.

    Opposite is happening in Australia ie since that is in the southern hemisphere.

    Implication is that the growth and slowing of the spread is only marginally affected by government policies to control the virus.

    it should be noted that in the US, at 235k deaths, the per capita death rate is appoximately 107% of the 1957 flu and 125% of the 1968 flu. Adjusting for the large increase on the % of the population over age 70 vs 1957 & 1968, the per capita death rate for most, if not all age groups, is less than both the 57 & 68 flu seasons.

    https://www.medrxiv.org/content/10.1101/2020.10.28.20221176v1.full.pdf+html

  43. The recent outbreak in Europe may be due to a mutation.

    Researchers from Basel and Spain have identified a novel SARS-CoV-2 variant that has spread widely across Europe in recent months, according to an un-peer-reviewed preprint released this week. While there is no evidence of this variant being more dangerous, its spread may give insights into the efficacy of travel policies adopted by European countries during the summer.

    https://medicalxpress.com/news/2020-10-sars-cov-variant-europe-summer.html

  44. Re the https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-930658 post:

    The new variant was first identified by Hodcroft during an analysis of Swiss sequences using the ‘Nextstrain’ platform, developed jointly by the University of Basel and the Fred Hutchinson Cancer Research center in Seattle, Washington. 20A.EU1 is characterized by mutations that modify amino-acids in the spike, nucleocapsid, and ORF14 proteins of the virus.

  45. Hmmm … where have I heard this before … dang .. can’t remember ….
    Now a new, peer-reviewed study in the International Journal of Antimicrobial Agents may add fuel to a fire that seemed to be burning out. The study finds that outpatients with the coronavirus who were treated with hydroxychloroquine combined with zinc and the antibiotic azithromycin were less likely to be hospitalized. Fewer than 3% of outpatients who took the drug regimen ended up in the hospital versus 15% who did not take it.

    A number of studies have found that hydroxychloroquine has no effect on inpatients. But critics have said that patients who are already in the hospital may be too sick for the drug to have any effect. Outpatients, they claim, often present with milder symptoms, and thus, hydroxychloroquine may prove effective.

    https://www.washingtonexaminer.com/news/study-shows-hydroxychloroquine-may-be-effective-for-outpatients-with-covid-19

  46. SOMEBODY STOLE THEIR TCELLS!!

    • Funny!
      So much for in-vitro studies that show expected T cell responses to SARS2 infection.

      If y’all are up to it I am working my way through this paper.
      https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385482/

      “These data identify defective Bcl-6+TFH cell generation and dysregulated humoral immune induction early in COVID-19 disease, providing a mechanistic explanation for the limited durability of antibody responses in coronavirus infections and suggest that achieving herd immunity through natural infection may be difficult.”

      As I have suggested, given that the duration of protective immunity conferred by infection is shorter than the pandemic episode “herd immunity” is invalid.

  47. I heard they had immunity

  48. Steven Mosher

    sweden loses its grip

    https://www.expressen.se/nyheter/coronaviruset/jatteokning-i-stockholm-vi-har-tappat-greppet/

    “Stricter advice
    On October 29, stricter general councils were introduced in Stockholm County, among other places. It is not yet visible in the numbers because it takes a while from the time someone is infected until the person gets symptoms, is tested, gets a positive test result and possibly is admitted to hospital.

    In the Uppsala Region, which was the first in the country to introduce stricter general guidelines on 20 October, the number of infected people has since increased sharply. But even there, it is not certain that the majority have been infected after the advice was introduced, according to the infection control doctor there.

    – We need to see that fewer people move around in society, that people avoid going to parties and being crowded in shops. It has to happen now, says Björn Eriksson.”

  49. > but deaths are still minimal:

    Deaths are 10 X per capita what they are in Finland.

  50. Steven Mosher

    Somebody tell the Swedish PM that
    Nic says nothing to be concerned about

    https://www.dn.se/sverige/lofven-antalet-avlidna-kommer-att-oka/

  51. Steven Mosher

    More from my buddy

  52. Steven Mosher

    • Steven –

      Hard to believe, but if I’m not mistaken Nic hasn’t posted anything in a while about Sweden even though things have changed quite a bit there since he asserted 5 months ago (was it 6?) that they’d reached “herd immunity” status.

      A while back he speculated that the increase in infections in Sweden might be a “blip.” I’m thinking that’s not very likely at this point.

      But why hasn’t Nic commented? S

      Seems to me thaast a serious scientist, he should be sure to clarify whether his theory has been falsified.

  53. Beware of Worldometer, the deaths are by date of reporting, not by actual date of death. The Wikipaedia page reports date of death. They do show cases soaring, but so far a small blip in admissions and deaths. Of course, predictions are hard, especially about the future.

    It seems to me that most everyone with flu experience predicted this winter second wave. It’s much worse in the rest of Europe BTW including in Germany which has been held up by Josh as a sterling example of how to “stamp” out the virus. This also shows that mask mandates are not predictive of a second wave.

    Odd that the laws of nature and epidemiology can’t be denied successfully by governments or non-scientists on the internet with too much time on their hands and nonexistent math skills. It’s a highly infectious virus and there is going to be excess mortality even though so far in the US its about 7% or so excess mortality. Expected mortality in the US is about 2.85 million per annum.

    Annual mortality per million has been decreasing in the West for 150 years thanks to the evils of fossil fuels and technology. 2020 looks about on track to be about equal to the average of the 1990’s. Tragic, but hardly an emergency.

    • > They do show cases soaring, but so far a small blip in admissions and deaths. Of course, predictions are hard, especially about the future.

      You said the pandemic was over in the US months ago. You dismissed the spike in cases in the US this summer as insignificant because the surge in cases, you asserted, were only among the young and/or because of an increase in testing.

      You didn’t caveat your assessment then because of uncertainty about the future.

      Interesting contrast.

      And your assertion of a “small blip” in hospitalizatons stands in contrast to what health officials in Sweden are saying.

      You never learn, do you?

    • > including in Germany which has been held up by Josh as a sterling example of how to “stamp” out the virus.

      I never said that.

    • Josh, I think you are just misremembering what I said. Earlier you cited some comments of mine that said nothing of the kind. I do believe its over in New York for example. I was thinking at one point that it was perhaps over in Europe, but that is now obviously not true. Elsewhere in the country, its not over yet even though in Texas and Florida, they seem to be over the hump of the second wave. It is true that fatality rates for those hospitalized has gone down dramatically indicating better treatment or that most new cases are younger people.

      In any case, you didn’t really respond to anything I said, you just deployed an evidence free ad hominum attack. Everyone (especially you) are wrong sometimes. So what?

      • David –

        > Josh, I think you are just misremembering what I said. Earlier you cited some comments of mine that said nothing of the kind.

        I provided quotes of the comments that proved you said what I said that you said. And after I provided you with those quotes you said nothing.

        >In any case, you didn’t really respond to anything I said, you just deployed an evidence free ad hominum attack.

        I explained that you were wrong in the arguments that you made previously. I’m sorry that you are a snowflake and don’t like being held accountable for past arguments that were wrong

        Meanwhile, I never said anything remotely like that Germany was an example of how to “stamp” out the virus.

        > Everyone (especially you) are wrong sometimes. So what?

        Exactly a perfect example of your problem. You made the same mistaken arguments previously that you making now. That’s the “so what.”. It isn’t just that you made mistaken arguments previously. It is that you made THE SAME mistaken arguments previously, duck accountability, and make the same mistaken argument again.

      • I’m not making any argument. I’m just citing statistics. Your comments are an attempt to discredit by throwing mud at the wall to see if anything will stick. You could actually try to engage without your hostile intent. A purely negative attack (and off the mark) on someone else is not a contribution, its what children do to adults who they don’t like.

      • Re: (Joshua) “Exactly a perfect example of your problem. You made the same mistaken arguments previously that you making now. That’s the “so what.”. It isn’t just that you made mistaken arguments previously. It is that you made THE SAME mistaken arguments previously, duck accountability, and make the same mistaken argument again.”

        Exactly. For example, he previously said:

        “There are at least now 10 more meaningful serological studies from around the world.
        1. There is a Danish one of blood donors Joshua pointed out. IFR is 0.08.
        2. There is the Santa Clara study which was strengthened by a revision.
        3. There is a Los Angeles County study which shows a low IFR too.
        4. Miami Dade county which shows an IFR of 0.17-0.31% even when I took fatalities from 21 days after the mean testing date.
        5. State of Arizona comes in around 0.28%.
        […]
        I personally think the US as a whole is more similar to the 4 US datasets I mentioned above.
        […]
        Using Ferguson’s IFR numbers by age cohort (which are probably at least a factor of 2 too high) […].”

        https://judithcurry.com/2020/05/06/covid-discussion-thread-vi/#comment-916993

        “There are by now at least 10 serologic data sets around the world. They pretty much uniformly show an IFR less than 0.5% with the best ones showing perhaps 0.12% to 0.31%.”
        https://statmodeling.stat.columbia.edu/2020/05/08/so-the-real-scandal-is-why-did-anyone-ever-listen-to-this-guy/#comment-1333886

        Almost every part of that is wrong.

        1) The Danish study he cites focuses on blood donors, which is a problem since blood donor studies tend to under-estimate IFR by over-estimating population-wide seroprevalence. For example, they exclude very young people and very old people, instead focusing on an age-range in which people are more likely to go out and interact with people, thereby being more likely to get infected:

        “Blood Donors. Only a small fraction of blood donors are ages 60 and above—a fundamental limitation in assessing COVID-19 prevalence and IFRs for older age groups—and the social behavior of blood donors may be systematically different from their peers.[13, 18] These concerns can be directly investigated by comparing alternative seroprevalence surveys of the same geographical location. As of early June, Public Health England (PHE) reported seroprevalence of 8·5% based on specimens from blood donors, whereas the U.K. Office of National Statistics (ONS) reported markedly lower seroprevalence of 5·4% (CI: 4·3–6·5%) based on its monitoring of a representative sample of the English population.[19, 20]”
        https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v7

        The Danish study dpy cites even leaves out those aged 70 and older. That under-estimates deaths and thus IFR, because older people are more likely to die of COVID-19. So it’s on par with saying ‘breast cancer is not that deadly’, by performing a study that disproportionately excludes older women. When the study’s authors updated their analysis to include those 70 and older, they got an IFR that contradicted dpy’s claim of a low IFR of <0.5%:

        old study: https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa849/5862661

        update:
        “The IFR for the adult Danish population aged 17 years or older was 0.81% (95% CI: 0.52%-2.2%).”
        https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa1627/5939898

        2) The Santa Clara study suffered from a number of crucial flaws, including a recruitment design that over-estimates population-wide seroprevalence, reportedly misleading statements used to recruit subjects, inadequate corrections for test sensitivity/specificity, test-adjusted seroprevalence that likely overlapps with 0%, funding issues, etc. See:

        https://www.scientificamerican.com/article/the-ioannidis-affair-a-tale-of-major-scientific-overreaction/ [ https://archive.is/wI9O3#selection-771.49-799.65 ]
        https://rapidreviewscovid19.mitpress.mit.edu/pub/p6tto8hl/release/1
        “Estimation without representation: Early SARS-CoV-2 seroprevalence studies and the path forward”
        “Bayesian analysis of tests with unknown specificity and sensitivity”
        “Estimation of COVID-19 prevalence from serology tests: A partial identification approach”
        Not yet peer-reviewed: “Estimating COVID-19 antibody seroprevalence in Santa Clara County, California. A re-analysis of Bendavid et al.”
        Under peer review: “Global seroprevalence of SARS-CoV-2 antibodies: a systematic review and meta-analysis”, page 40 of supplementary materials
        In press: “Assessing the age specificity of infection fatality rates for COVID-19: Meta-analysis & public policy implications”

        https://buzzfeednews.com/article/stephaniemlee/stanford-coronavirus-neeleman-ioannidis-whistleblower
        https://buzzfeednews.com/article/stephaniemlee/stanford-coronavirus-study-bhattacharya-email

        3) The Los Angeles County study was done during an accelerating outbreak where deaths are difficult to match with infections, making its IFR from it less reliable. It also over-estimated population-wide seroprevalence by not paying sufficient attention to how test characteristics changed when applied to people at different times post-infection:

        “By contrast, matching prevalence estimates with subsequent fatalities is not feasible if a seroprevalence study was conducted in the midst of an accelerating outbreak.”
        “H.2: Studies excluded due to accelerating outbreak
        […]
        Los Angeles, California, USA”

        https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v7.supplementary-material

        Under peer review: “Global seroprevalence of SARS-CoV-2 antibodies: a systematic review and meta-analysis”, page 36 of supplementary materials

        4) The Miami-Dade researchers later decreased their seroprevalence estimate from 6% (thereby increasing any IFR estimated from it), possibly due to issues with their original testing protocol:

        old: https://miamidade.gov/releases/2020-04-24-sample-testing-results.asp
        new: https://web.archive.org/web/20200727041934/http://www.sparkc.info/

        5) There’s no evidence I know of that the Arizona results were from a randomized sample representative of the general population in Arizona:

        6) We now also have other studies from different parts of the US showing an IFR of 0.5% or more. Some examples:

        1.6% (~0.6% IFR when corrected using the supplementary materials cited above for Los Angeles County) : https://wwwnc.cdc.gov/eid/article/26/11/20-3029_article
        1.3% : https://louisville.edu/medicine/news/phase-ii-results-of-co-immunity-project-show-higher-than-expected-rates-of-exposure-to-novel-coronavirus-in-jefferson-county
        0.8% (higher, if one accounts for right-censoring) : https://washoecounty.us/outreach/2020/07/2020-07-08-jic-update-0708.php
        0.6% (higher, if one accounts for right-censoring) : https://sciencedirect.com/science/article/pii/S1047279720302015
        0.6% (higher, if one accounts for right-censoring) : https://cdc.gov/mmwr/volumes/69/wr/mm6929e1.htm
        consistent with 0.5% – 1.0% : http://archive.is/JXtUt#selection-1159.0-1163.200 [ https://rivcoph.org/Portals/0/Documents/CoronaVirus/July/News/7.27.20%20antibody%20testing%20results.pdf?ver=2020-07-27-144931-703&timestamp=1595886602504 ]

        Hence why the CDC upgraded their best estimate of IFR to ~0.7%, even though that’s also likely an under-estimate, as acknowledged by a soon-to-be-updated draft of the study they cite for that estimate:

        I’ve also already gone over how one can tell USA-wide IFR was >0.5% up to July/August:

        7) And Ferguson et al.’s age-specific IFRs turned out pretty, as opposed to dpy’s claim of them by 2X too high population-wide. In contrast, Nic Lewis’ age-specific IFR analysis was a disaster:

        Ferguson et al.’s population-wide IFR was 0.9% for Great Britain:

        “[…] when applied to the GB population result in an IFR of 0.9% […]”
        https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/

        That largely matches estimates for England and Great Britain in the range of 0.8% – 1.4% for average IFR. In fact, Ferguson et al. may have even under-estimated IFR:

        https://doi.org/10.1016/S2468-2667(20)30135-3
        “A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates”, figure 3
        In press: “Assessing the age specificity of infection fatality rates for COVID-19: Meta-analysis & public policy implications”, figure 6 and supplementary appendix M
        Under peer review: “Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults”, supplementary table S2a

        Maybe at some point various right-wingers like dpy, Nic Lewis, etc. will stop misleadingly downplaying the pandemic’s severity in order to avoid policies they dislike (ex: lockdowns). Also, Joshua, I already know I’m not going to get a cogent response from him on any of this, because a cogent response would require him to actually read the material and studies in question.

    • David –

      Here’s what you had to say:

      > They do show cases soaring, but so far a small blip in admissions and deaths.

      Here’s what people actually knowledgeable about what’s going on in Sweden have to say:

      > “There is continued increase in the number of cases in all regions except one,” said Karin Tegmark Wisell, head of the microbiology department at the agency.

      “We are now also beginning to see a fairly significant increase on the number of intensive care patients.”

      The intensifying outbreak has seen Sweden tighten the mostly voluntary recommendations on which it relies across much of the country and Tegmark Wisell said the percentage of positive tests had climbed to 9.7% last week from 5.6% the week before.

      Earlier on Thursday, Swedish Prime Minister Stefan Lofven said he was self-isolating and getting tested after he learned a person close to him had met someone who was later confirmed to have COVID-19.

      On Thursday, 90 COVID-19 patients were receiving intensive care at Swedish hospitals, 19 more than on Wednesday, while a further 661 were being treated in other modes of care

  54. Dpy said:

    > dpy6629 | July 27, 2020 at 9:34 pm |
    Bear in mind that total cases in Florida and Texas are still vastly lower than in New York.

    I said:

    > 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,

    ——

    Dpy said:

    > dpy6629 | July 28, 2020 at 11:44 am |
    Of course testing in Florida and Texas testing is vastly more extensive than in New York

    I said:
    > 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

    ——

    > dpy6629 | July 4, 2020 at 11:06 pm |
    Don is right of course. This is why cases are rising strongly in the US but deaths are on a downtrend.

    Check out what happened to the US death trend after June 4th (after you said deaths are in a downward trend they went up 400% immediately after and are still > 3 X higher).

    https://www.worldometers.info/coronavirus/country/us/

    You keep making the same mistake, David. Why don’t you learn?

  55. Dpy said:

    > dpy6629 | July 27, 2020 at 9:34 pm |
    Bear in mind that total cases in Florida and Texas are still vastly lower than in New York.

    I said:

    > 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,

    ——

    Dpy said:

    > dpy6629 | July 28, 2020 at 11:44 am |
    Of course testing in Florida and Texas testing is vastly more extensive than in New York

    I said:
    > 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

    ——

    > dpy6629 | July 4, 2020 at 11:06 pm |
    Don is right of course. This is why cases are rising strongly in the US but deaths are on a downtrend.

    Check out what happened to the US death trend after June 4th (after you said deaths are in a downward trend they went up 400% immediately after and are still > 3 X higher).

    You keep making the same mistake, David. Why don’t you learn?

    • Oops. Sorry, that should have been double immediately and up 50% now.

    • Nic is entirely correct that Josh provides little of value. He quotes stuff that is just a cloud of words that may or may not contradict what someone else says. Josh, you are a verbose but unenlightening quote miner with vastly too much time on your hands. Put down the laptop for a week and actually read some of the science in detail so you can make it worth others while to read your comments.

    • You are just lying about what I meant. Testing is vastly more common in Texas and Florida now than at the height of the New York epidemic when tests were scarce. It means nothing to compare total tests in New York and Texas and Florida because of this factor. Vast numbers of infections were missed in New York. Now that number is much much lower in Texas and Florida. You think you are disproving what someone else said without first thinking clearly about what the context is. That’s childish and not worth even reading. It’s stupidly literalminded too.

  56. Nic’s toy model is more accurate than Nate Silver’s 538 polls. :)

  57. Forget lock downs, vaccines & masks. Looks like the Danes are not taking any chances (how to achieve instant herd immunity).

    “Denmark is culling its entire mink farm population
    The mink outbreaks are “spillover” from the human pandemic—a zoonosis in reverse that has offered scientists in the Netherlands a unique chance to study how the virus jumps between species and burns through large animal populations.”
    https://www.sciencemag.org/news/2020/06/coronavirus-rips-through-dutch-mink-farms-triggering-culls-prevent-human-infections

  58. Let it be a warning. They weren’t testing enough to catch the outbreak and it exploded. Our industrial farm factory model relies too much on antibiotics and not testing to quickly remove the infected from the population.
    I want a smart watch that can constantly monitor me for infections diseases.

  59. Imagine how bad it might be in Sweden if they hadn’t reached a “herd immunity threshold” 5 months ago:

    -snip-

    STOCKHOLM — Sweden, whose soft-touch virus approach has placed it in the global spotlight, recorded new 15,779 COVID-19 cases on Tuesday as a resurgent pandemic stretched testing to the limit in many hard-hit and densely populated regions.

    The increase since the Health Agency’s previous update on Friday compared with a 10,177 case jump for the corresponding period last week. Cases in Sweden, which does not publish data over the weekend or Mondays, have repeatedly hit daily records over the last two weeks.

    “We can see that the increase is evident in all age groups,” Health Agency official Sara Byfors told a news conference.

    “Like the other curves, deaths are also heading higher, though not as steeply yet.”

    Sweden also tightened recommendations for three more regions on Tuesday, meaning inhabitants in 13 out of 21 regions now are advised to work from home, avoid public transport and limit social interaction outside the family as much as possible.

    […]

    Sweden registered 35 new deaths on Tuesday, taking the total to 6,057 during the pandemic. Sweden’s death rate per capita is several times higher than Nordic neighbors but lower than some larger European countries, such as Spain and Britain.

    https://canoe.com/news/world/swedish-covid-19-cases-surge-as-testing-struggles-to-keep-up

  60. Why hasn’t Nic commented?

    Have the recent developments in Sweden falsified his assertion that they reached a herd immunity threshold 5 (6?) months ago?

    At what point would his assertion be falsified? His modeling proved wrong?

    Why hasn’t he commented?

  61. Why does Nic Lewis seem to hang gone mum on the situation with Covid in Sweden?

    > The Swedish government has proposed a stop to the sale of alcohol after 10pm as the Prime Minister warned that too many people had relaxed when it came to following coronavirus recommendations.

  62. Surely the end of the debate over herd whether herd immunity has helped the 2nd wave in Sweden…

    https://www.theguardian.com/world/2020/nov/12/covid-infections-in-sweden-surge-dashing-hopes-of-herd-immunity

    I wouldn’t say this proves Sweden strategy overall was wrong, just that the claims of herd immunity were clearly incorrect. It’s also clearly true that compared to other Scandi countries, many more people have died.

    Whether alternatives elsewhere are better overall can never be more than opinion. Personally, I’d much rather have lived through this in Copenhagen or Helsinki than Stockholm, from what I can gather of the different approaches, disease impacts and restrictions (I know a lot of Swedes, but not many people from the rest of Scandinavia).

    • > I wouldn’t say this proves Sweden strategy overall was wrong.

      Not would I. Ultimately that is up to the people of Sweden to decide, obviously. Perhaps if they had devoted more resources to protecting older people in elder housing their results could have been significantly better than they have been.

      Nonetheless, there don’t seem to be obvious economic benefits to their approach (as the herd immunity crowd assumes without evidence) and Sweden is clearly better suited to a “iight touch” approach than countries like the US (with higher population density, more people per household, poorer baseline health, fewer % of people able to work from home, etc.).

      All adds up to poor analysis from the “Thank God for Sweden” crowd. And climate “skeptics” as a group. But what else is new?

  63. Wow – I had no idea this thread was still running :-)

    Anyway, it is interesting that Sweden’s deaths per capita is about 1/15th what it was during the spring peak, even though the cases per capita is the same. I don’t know if they’ve killed off a high percentage of vulnerable or what – but certainly the vulnerable remaining are much better protected than in the spring. A caveat – it takes quite awhile from infection to death, so current deaths are from when the infection rate was significantly lower. Their infection rate is going up very rapidly – doubling every 9 days implies (roughly) an Rt of about 1.5.

    That Rt sure doesn’t look like herd immunity is doing much, unless everyone is actively going out and kissing everyone else or something.

    • meso –

      > Anyway, it is interesting that Sweden’s deaths per capita is about 1/15th what it was during the spring peak, even though the cases per capita is the same. I don’t know if they’ve killed off a high percentage of vulnerable or what – but certainly the vulnerable remaining are much better protected than in the spring.

      There are clearly use identifying a higher % of the positive cases. So the comparison is fraught.

      >A caveat – it takes quite awhile from infection to death, so current deaths are from when the infection rate was significantly lower. Their infection rate is going up very rapidly – doubling every 9 days implies (roughly) an Rt of about 1.5.

      Their per capita death rate will be rising…

      -snip-

      The number of patients hospitalised with Covid-19 is doubling in Sweden every eight days currently, the fastest rate for any European country for which data is available.

      -snip-

      https://www.google.com/amp/s/amp.ft.com/content/1e0ac31d-5abf-4a18-ab3e-eec9744a4d31

      • Joshua, I don’t understand your comment about a higher percentage of cases. Are you saying that they now identify more of the COVID19 deaths as COVID19? If so, then things are even better, comparatively, than in the spring.

      • Yes. They are capturing a higher % of the infections. So the comparison to earlier is fraught. Even though it might look like there are more cases now because the # of positive tests is muxh higher, in the earlier spike there were more undetected cases so the number of infections is actually probably comparable.

        In one sense, sure, it’s a good thing thst they are capturing a higher % of the infections.

        But here’s the downside. It means that the high number of positive tests relative to a low death rate (as for now) isn’t explained (only) by a lower IFR. It means that the different rates of growth aren’t largely explained by having “killed off” the vulnerable people or having gotten better at protecting the vulnerable people. It seems that they see again getting a lot of infections in elder housing. IOW, we can expect the death rate to begin approaching the death rate from the earlier wave. Probably? not as high because yes, the IFR is lower. But still it will likely climb by quite a bit. The hospitalizations and ICU admissions are already starting to climb.

      • They now are capturing 4x as many infections total and 5x as many of the cases that are out there. Means not as many true infections as before but close. And sure the IFR is lower, but how much lower, really? Better at protecting vulnerable people or fewer vulnerable people to get infected? Possible. I wouldn’t bet on it. We’ll wait another 4 weeks and find out.

      • Joshua – where are you getting the ascertainment rate? I just don’t have that available in the sources I use.

        I would be surprised if the IFR isn’t lower for real, as opposed to a measurement artifact. One would expect fewer high risk people are being exposed – at least one would hope that. Plus, treatment has gotten significantly better since the spring. Also, if there is more mask wear, that may make infections less serious – if.

        Do you have data on the percentage of high risk being exposed now as opposed to the past?

      • meso –

        I’m going with the ascertainment rate from what Bevand says. He could be wrong but from what I’ve seen has a good track record.

        > I would be surprised if the IFR isn’t lower for real, as opposed to a measurement artifact.

        Of course. I said that explicitly.

        The question is how much the divergence between the positive test rate and death rate is explainable by a lower infection fatality rate as opposed to true case fatality rate.

        > Do you have data on the percentage of high risk being exposed now as opposed to the past?

        Not data, but there is some limited evidence. Of course it stands to reason that in skmw ways it would get better. But there are structural problems. A lot of the employees in those institutions live in households of many relatively poor immigrants and with a high spread in larger society you should expect crossover into elder housing. Do you really think this “just protect the vulnerable” rhetoric is realistic?

        -snip-

        Earlier Wednesday, the Swedish capital reintroduced a ban on visiting elderly care homes after a coronavirus spike was reported in retirement facilities in Stockholm

        https://medicalxpress.com/news/2020-11-sweden-sale-alcohol-10pm-curb.html

      • Plus look at the growth rate in hospital admissions and ICU admissions. Stands to reason that there will be an increase in the ratio of ICU admissions to deaths rate – but by how much? ICU admissions are bad in and of themselves, but there is every reason to think their death rate will be increasing. Look at death rate now compared to Nordic neighbors. It’s spreading more rapidly – but in line with Sweden being behind on the curve. Tegnell said as much:

      • Joshua – I’m not arguing with you. I’m just trying to explore things.

        You ask: “Do you really think this “just protect the vulnerable” rhetoric is realistic? ”

        No, I don’t. I have never thought it was realistic. If we could really do that well, we could more or less just let the virus rip. But we can’t, and in the US in particular, too many people are in high risk categories, plus as you say, many are living with high risk people.

        Also, as the viral prevalence grows, so do the odds of infection even when care is being taken – because nothing is perfect.

        Care homes are especially vulnerable because of the need of carers – who apparently can’t just be locked into the care home in an impermeable bubble.

        Also, while spread through surfaces has been downplayed, it is still a factor. Higher prevalence increases the odds that food or other supplies are contaminated.

        And, sometimes outsiders must come in to a care home or just the home of vulnerable people. For example, if a necessary appliance breaks down, someone has to fix it.

        Then there is medical care – more likely needed by those who are vulnerable.

        If we thought the disease would be with us forever – no vaccine, no effective treatment – then we might have to create more effective bubbles. But that would be expensive and take a lot of time.

        So no – “just protect the vulnerable” is a nice slogan completely out of touch with reality.

      • meso –

        I agree with you on all of that.

        If people really were serious about paying vulnerable people to stay home and not work, and providing comprehensive services for grandparent-caregivers including alternate caregiving resources, and providing seniors the ability to get safe transport to medical care, and and giving comprehensive support to employees in nursing facilities or other senior housing (so they could stay on site maybe for a week and then alternate), and provide massive levels of testing and contract tracing, etc., then I agree that “protecting the vulnerable” could at least be an honest discussion and worth having.

        But many of the people promoting that approach are the very same people who would squeal like stuck pigs about providing the massive funding and centralized government resources need to pull something like that off.

        And so yeah, it’s just a convenient slogan – that mostly just serves as a proxy for partisan warfare. Sometimes i just sit back and shake my head at just how far we’ve devolved as a society. Even a pandemic becomes fodder for political identity warfare.

  64. My image from the last didn’t make it – see https://ibb.co/JjsfLrh

    here

  65. Here’s the same graph with US data and Sweden data for comparison.

  66. Where’s Nic?

    • Re: “Where’s Nic?”

      Not here addressing his false claims on seroprevalence, IFR (infection fatality rate), herd immunity, etc. And I thought you might find this of interest, Joshua.

      Nic Lewis wrote this above:
      “If the sample is representative of the Tokyo metropolitan area, which the authors suggest it may be, that implies seroconversion of about 5.7 million individuals during the study period.
      Since the corresponding number of deaths attributed to COVID-19 appears to have been little more than 30, that implies an infection fatality rate in Tokyo that might be as low as 0.0006% – around a thousand times lower than generally estimated.”

      Of course, that fails since that sample is not representative of Tokyo. It’s non-randomized sampling of a company, and recruits volunteers who are more likely to want to be tested because of a workplace outbreak. So it’s not a probability sample and not all that interesting. However, there is a more randomized and representative sample for Tokyo + Osaka + Miyagi, which implies an IFR of ~1.3%. That’s a few orders of magnitude larger than the IFR Lewis posted above:

      It’s higher than IFR results coming from Sweden, a region where Lewis also under-estimates IFR:

      Lewis’ words:
      ” The Stockholm infection fatality rate appears to be approximately 0.4%,[20] considerably lower than per the Verity et al.[21] estimates used in Ferguson20″
      https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/

      Public Health Agency of Sweden:
      “Globally, it is estimated that 0.5–1 percent of those who are infected with COVID-19 die.”
      https://folkhalsomyndigheten.se/the-public-health-agency-of-sweden/communicable-disease-control/covid-19/

      Public Health Agency of Sweden (discussing IFR for Stockholm):
      “Our point estimate of the infection fatality rate is 0.6%, with a 95% confidence interval of 0.4–1.1%.”

      Click to access infection-fatality-rate-covid-19-stockholm-technical-report.pdf

      On IFR for Stockholm:
      “The infection fatality ratio extrapolates to 0.61% (peak: 1.34%).”
      https://medrxiv.org/content/10.1101/2020.06.30.20143487v2.full

      Lewis was using a seroprevalence of ~17% for Stockholm to get his “0.4%” IFR estimate, when he doesn’t have any evidence that 17% came from a representative/randomized sample, or a probability sample. There was a probability sample for Stockholm, however, with a lower seroprevalence estimate of ~10% in April and ~11% in May:

      https://www.medrxiv.org/content/10.1101/2020.07.01.20143966v1.full

      That seroprevalence gives you ~253,000 infections in May. If you look at deaths in June to account for lag between seroconversion and deaths, you get ~2160 COVID-19 deaths:

      https://www.sll.se/verksamhet/halsa-och-vard/nyheter-halsa-och-vard/2020/06/8-juni-lagesrapport-om-arbetet-med-det-nya-coronaviruset/

      That number of deaths and infections implies an IFR of ~0.9%, or about double what Lewis claimed. And, of course, Lewis also used ~8 deaths on the Diamond Princess to infer a fatality rate, when almost double that number (14) actually died:

      “[…] the 14 deaths already recorded […]”
      https://science.sciencemag.org/content/368/6498/eabd4246

      Lewis’ words:
      “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%, giving an estimated ultimate death toll of 8.34, allocated as to 3.58 to the 70-79 age group and 4.77 to the 80+ age group.
      Accordingly, the Verity et al central estimate for the Diamond Princess death toll, of 12.5 eventual deaths, is 50% too high. This necessarily means that the estimates of tCFR and sCFR they derived from it are too high by the same proportion.”

      https://judithcurry.com/2020/03/25/covid-19-updated-data-implies-that-uk-modelling-hugely-overestimates-the-expected-death-rates-from-infection/

      Lewis sure does under-estimate IFR a lot, huh? He does that in a way that conveniently makes SARS-CoV-2 + COVID-19 look less dangerous than they actually are, and makes policy responses like lockdowns look less necessary. I wonder why he does that. I also wonder why many late 20th century political conservatives who opposed public smoking bans, cigarette taxes, etc., kept making smoking + second-hand smoking less dangerous than they actually were. One would need to be a genius to figure out why these sorts of things happen.

  67. Nic speculated that herd immunity could be reached at very low levels

    ~20%

    Somebody tell these people

    https://www.medrxiv.org/content/10.1101/2020.11.02.20224782v1.full

    Now, THEORETICALLY “herd immunity” could be reached at very low levels of prevalence BUT it would require a population that wasn’t mixing–
    contacting each other. AND to be sure some regions will have people in more contact and some areas will have less mixing. And some people will encounter few humans, while other contact 1000s.

    The abstraction of “herd imunnity” is not something you can measure, not something you can use for precise public policy.

    and NO sweden did not achieve herd immunity months ago as nic claimed.

    • Re: “Somebody tell these people”

      Or any of the numerous other regions with >40% seroprevalence. For instance:

      Lewis’ core distortion on herd immunity is pretty obvious, if one is familiar with the relevant biological concepts. You can see it in the quotes from him below:

      “Yet recorded new cases had stopped increasing by 11 April (Figure 1), as had net hospital admissions,[6] and both measures have fallen significantly since. That pattern indicates that the HIT had been reached by 11April, at which point only 17% of the population appear to have been infected.”
      https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/

      “Notwithstanding that a month ago antibodies were only detected in 6.3% of the Swedish population, the declining death rate since mid-May strongly suggests that the herd immunity threshold had been surpassed in the three largest regions, and in Sweden as a whole, by the end of April.”
      https://judithcurry.com/2020/06/28/the-progress-of-the-covid-19-epidemic-in-sweden-an-analysis/

      So Lewis assumed that a reduction in cases/day, hospitalizations/day, and COVID-19 deaths/day means the herd immunity threshold (HIT) was reached. But it doesn’t mean that, and his claim that it does shows that he doesn’t understand what herd immunity is at even an elementary level.

      The point with herd immunity is that the proportion of people immune to infection is enough prevent the virus from finding enough people to use to infect others, thus keeping R below 1 without the aid of additional factors beyond those already present at baseline. So herd immunity is about R staying below 1 even under baseline conditions of no additional behavior changes and no additional public health interventions. That’s why HIT is calculated in terms of R0 (the basic reproduction number), or under baseline conditions with no new behavior changes + no additional public health interventions (ex: without increased mask-wearing, lockdowns, etc.), as opposed to with R when those additional factors are in play. For example, see:

      Pre-print: “High SARS-CoV-2 seroprevalence in children and adults in the Austrian ski resort Ischgl” (with: https://videocast.nih.gov/watch%3D38084, from 40:29 – 42:02)
      Pre-print: pages 1 and 8 of “The reproduction number of COVID-19 and its correlation with public health interventions”
      “Herd immunity: Understanding COVID-19”
      “Herd immunity – estimating the level required to halt the COVID-19 epidemics in affected countries”
      “Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period”
      Pre-print: “Estimating hidden asymptomatics, herd immunity threshold and lockdown effects using a COVID-19 specific model”
      Pre-print: “Moving beyond a peak mentality: Plateaus, shoulders, oscillations and other ‘anomalous’ behavior-driven shapes in COVID-19 outbreaks”
      Pre-print: “Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?”

      But Stockholm, and Sweden in general, were not at baseline conditions at the point Lewis claim they reached HIT. After all, new behavior changes and additional public health interventions had occurred. For example:

      – the level of mobility / social interaction dropped
      – high schools and universities were closed
      – very large gatherings were closed

      And so on. That’s covered in sources such as:

      http://archive.is/yo5Ac
      “Managing COVID-19 spread with voluntary public-health measures: Sweden as a case study for pandemic control”
      “Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe” (pages 27 – 30 of Supplementary Information)
      “Quantifying the impact of non-pharmaceutical interventions during the COVID-19 outbreak – The case of Sweden”
      Pre-print: “How did governmental interventions affect the spread of COVID-19 in European countries?”

      That wasn’t a full lockdown, but it was enough to force Sweden out of baseline conditions of R0, at the expense of a greater rate of infection, with greater COVID-19 deaths per capita and greater excess deaths, than countries that promptly locked down, like Denmark, Finland, and Norway.

      Lewis’ distortion was conflating the effect of those public health interventions + behavior changes, with the effect of herd immunity. That’s dangerous. For instance, if HIT really was achieved, then getting back closer to baseline by removing some of those behavior changes and public health interventions would still keep R below 1, with no increase in cases/day. However, if herd immunity had not been reached, then removing those behavior changes and interventions would cause cases/day to spike, followed by hospitalizations/day spiking, followed by deaths/day spiking, as R went back above 1. Technically, you wouldn’t even need hospitalizations/day and deaths/day to spike, since HIT is about R, and R is about infections. not necessarily whether those infections lead to people getting sick and/or dying.

      Anyway, I cited sources on this weeks ago, which Lewis simply ignored:

      https://judithcurry.com/2020/06/28/the-progress-of-the-covid-19-epidemic-in-sweden-an-analysis/#comment-920123

      “These early onset peak rates should arise not because of herd immunity but because of changes in behavior. […]
      The peaks occur at levels of infection far from that associated with herd immunity. Post-peak, shoulders and plateaus emerge because of the balance between relaxation of awareness-based distancing (which leads to increases in cases and deaths) and an increase in awareness in response to increases in cases and deaths.”

      https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273247/

      “This allows us to “bend the curve” and predict temporary equilibrium states, far away from the equilibrium state of herd immunity, but stable under current conditions […]. Yet, these states can quickly become unstable again once the current regulations change.
      https://link.springer.com/article/10.1007/s00466-020-01880-8

      So what happened in Stockholm, and Sweden overall? Exactly what’d you’d expect with no herd immunity. People spent more time indoors as the weather got colder, and so on, removing some of the behavior changes / interventions that kept spread of the virus in check. So cases/day spiked, then hospitalizations/day, then deaths/day, as people went through the typical process of getting infecting, then getting sick from the infection, and then dying from that sickness. And that further exposes the benefits of the policies pursued by the Nordic countries Finland, Norway, and Denmark, in comparison to Sweden.

      In May when I first responded to Lewis on herd immunity, I tried to explain his distortions to him in terms a biologist or epidemiologist would understand:

      https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/#comment-916999

      That was a mistake; I shouldn’t have assumed he could follow along with the biology, let alone should I have assumed that he knew what “herd immunity” was. At this point, it’s clear he was confused about the very basics of the biological concepts he was misusing. And that led him to defend a position that literally kills people by downplaying how many people SARS-CoV-2 can infect. His distortions conveniently fit with his ideology (ex: his opposition to government interventions like lockdowns) One could wonder if Lewis does the same thing when he downplays anthropogenic climate change in a way that conveniently suits his ideology. I wonder how many excess deaths that would lead to.

      This entire episode is a great example of the dangers of ideologically-motivated epistemic trespassing, and why it’s usually wise to leave topics like public health, immunology, epidemiology, etc. to those who actually know what they’re talking about.

      • And looks like Sweden’s government / public health officials accept that it’s public health interventions + behavior changes that are going to get them out of this, not herd immunity. Those changes are going to be enforced, Lewis should finally learn that lesson.

        “Sweden on Monday announced a ban on public events of more than eight people at a press conference where ministers urged the population to “do the right thing”.
        […]
        The new limit is part of the Public Order Act and therefore is a law, not a recommendation like many of Sweden’s coronavirus measures. People who violate the ban by organising larger events could face fines or even imprisonment of up to six months.”

        https://www.thelocal.se/20201116/breaking-sweden-introduces-limit-of-eight-coronavirus

        https://www.thelocal.se/20201116/explained-what-does-swedens-new-limit-on-public-events-actually-mean

      • Thanks for all the links…

        In a conversation with me, Nic eventually had to assert that the HIT is dependent on behavior, and thus changes. While there is something close to the herd immunity concept that is consistent with this, overall it as a silly redefinition, and one in conflict with the conventional understanding of the term, and the reason it is used.

        Sure, any time the infection rate turns around for awhile, one might think it is because HIT has been reached *for the current level of interactions*. And that might be true, although the peaks is more likely due to change in behavior in response to the rise. But even if it is a result of an increase in immunity, it is playing way too loose with the concept of herd immunity to be of any value.

      • Re: “In a conversation with me, Nic eventually had to assert that the HIT is dependent on behavior, and thus changes. While there is something close to the herd immunity concept that is consistent with this, overall it as a silly redefinition, and one in conflict with the conventional understanding of the term, and the reason it is used.”

        This was covered in the Ferguson et al. Report #9 from March that Lewis habitually distorted. So Lewis has no excuse for not being aware of it. It’s almost as if the experts with a background in this field knew more than ideologically-motivated right-wing non-experts. Anyway, HIT is calculated from R0, and R0 is for baseline conditions in the absence of additional/new public health interventions + in the absence of new behavior changes:

        “In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic”
        https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/

        “Assuming a uniform herd immunity threshold of 67% (R0 = 3) and an IFR of 0.6%, the absolute number of expected deaths across the globe would exceed 30 million people (Figure 2C).”
        https://www.sciencedirect.com/science/article/pii/S1074761320301709

        “A method is presented for estimating the model parameters from real-world data. It is shown that increase of infections slows down and herd immunity is achieved when symptomatic patients are 4-6% of the population for the European countries we studied, when the total infected fraction is between 50-56%.”
        https://arxiv.org/abs/2006.00045

        So Lewis’ proposed herd immunity threshold of 17% (7% – 24%) is non-expert nonsense. That makes it all the more telling when Lewis says stuff like this:

        “it’s good to see that some politicians have a decent understanding of these important issues, and terrifying to see how poor the understanding of them is by supposed scientific experts who control or influence polic policy, and how unwilling such ‘experts’ are to change their views as the evidence against them builds.”
        https://judithcurry.com/2020/09/22/herd-immunity-to-covid-19-and-pre-existing-immune-responses/#comment-927786

        “You’ve made multiple confused, invalid comparisons. I’m not going to waste my time demolishing them.”
        https://judithcurry.com/2020/06/28/the-progress-of-the-covid-19-epidemic-in-sweden-an-analysis/#comment-920103

        I wonder how Lewis will come to terms (if he ever comes to terms) with the fact that the politicians who’s previous views he defended, now “change[d] their views as the evidence against them builds”:

        “Sweden on Monday announced a ban on public events of more than eight people at a press conference where ministers urged the population to “do the right thing”.
        […]
        The new limit is part of the Public Order Act and therefore is a law, not a recommendation like many of Sweden’s coronavirus measures. People who violate the ban by organising larger events could face fines or even imprisonment of up to six months.”

        https://www.thelocal.se/20201116/breaking-sweden-introduces-limit-of-eight-coronavirus

        https://www.thelocal.se/20201116/explained-what-does-swedens-new-limit-on-public-events-actually-mean

      • Atomsk’s Sanakan – replying to your latest…

        While the HIT is calculated nominally as 1 – 1/R0, there have been a number of model-based papers suggesting that the effective HIT will be in the presence of various non-homogeneities – such as differing individual susceptibility, differing interpersonal contact patterns, etc. I would be interested in your comments on this general idea. See for example this recent paper: https://www.mpg.de/15962200/heterogenous-population-herd-immunity

        The standard HIT formula assumes that the population statistics in that regard do not change as the epidemic progresses – other than the transitions of individuals from susceptible to not-susceptible (see discussion in that paper). Authors have suggested that high spread paths may “burn out” – be removed from the susceptibility pool – after which the Rt would drop more than the basic HIT formula suggests. There are complexities. For example, R0 is calculated from an epidemic in actual subjects, so even as it is calculated, inhomogeneities that remain constant are taken into account.

        I am a non-expert, although I’ve done modeling professionally in the past. So I wonder if there is merit to those ideas – if epidemics in practice have shown such trajectories – if we can even tell.

      • Re: “While the HIT is calculated nominally as 1 – 1/R0, there have been a number of model-based papers suggesting that the effective HIT will be in the presence of various non-homogeneities – such as differing individual susceptibility, differing interpersonal contact patterns, etc. I would be interested in your comments on this general idea. See for example this recent paper:”

        They’re thought experiments, based on a conditional:
        ‘If X, then HIT would be beneath 40%’.

        That conditional might be true, even if X is false. One of my favorite examples of this was when the denialist Sunetra Gupta claimed that if 50% of people were immune to infection, then HIT would be lower, even though the evidence already clearly showed 50% of people were not immune to infection (yes, Gupta is a denialist, based on other ludicrous claims she’s made that run contrary to the evidence):

        If people instead move on to an “X” of “large differences in interpersonal contact patterns”, then those differences are nowhere near what we see for STIs, where HIT is substantially lower than in a homogenous scenario. Sex is a very particular act that many people can avoid (setting aside cases of rape, etc.), just like IV drug use, etc. There are also differences in the risk of transmission between different sex acts and between different means of using IV drugs (ex: via a ‘clean needles’ program). So that introduces a large amount of heterogeneity in the transmission of HIV and other STIs that can also spread by IV drug use.

        However, spreading of droplets and aerosols for respiratory viruses, is based on a very generalized behavior that virtually everyone does. So you’re not going to get as much heterogeneity introduced in. There might be some heterogeneity from healthcare professionals being more likely to be in contact with sick people (ex: during intubation that produces lots of aerosols), etc., but that’s going to be nowhere near what you need to drop HIT to below 40%, let alone to ~20%. That’s what the sources I cited above meant when they said a very low HIT does not make sense for a respiratory virus, in contrast to for an STI like HIV.

        Sometimes the conditional people use isn’t even true, such as when some people claim that T cell immunity, or cross-reactive T cell immunity, would substantially lower HIT beyond what’s seen with antibody production. That makes no sense to anyone with a basic understanding of how the T cell receptor and B cell receptor (TCR and BCR, respectively) work. This is one reason why it’s tedious dealing with non-expert ideologues like Lewis, who don’t grasp immunology at even a basic level nor bother relying on those that do.

        The TCR’s primary job is not to prevent re-infection, but instead to deal with an ongoing infection, either by killing virus-infected cells in the case of CD8+ T cells, or stimulating other immune cell responses in the case of CD4+ T cells. In contrast, one primary job of the BCR (and thus of antibodies since antibodies are basically soluble BCRs) is to prevent infection. Thus it would be antibodies and the BCR, along with the innate immune system / mucosal barrier functions / etc., that would play a role in limiting HIT by making people immune to infection, not T cells:

        And I already went over above why the claims on cross-reactivity don’t work:

        https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-929118

        So basically: people shouldn’t claim a HIT is actually low based on conditional statements that hinge on claims we know are false. That’s especially the case when we already see SARS-CoV-2 infect a larger proportion of people than a low HIT would predict (see the thread below). Thus, the idea of a low HIT substantially below 40% is dead, as far as I’m concerned. People can make as many models as they want based on conditional statements. If they don’t know the biology nor rely on those who do know the biology, then they’re offering hypotheticals that won’t happen because they violate well-evidenced biology.

        Yes, there’s some heterogeneity that reduces HIT a bit. No, it isn’t anywhere near what’s needed to drive HIT substantially below 40%. HIT is mostly likely 50% or more in most areas, unless their baseline conditions gave them a lower R0. The homogeneity assumption isn’t perfect, but it’s a decent and informative approximation for respiratory viruses like SARS-CoV-2.

      • Regarding the heterogeneity of contact patterns, I think you underestimate the variation of risks that exist. Some people are far more likely to encounter infected people (via airborne spread) than others. I sing in a church choir – or did until COVID19 appeared, at which point I quit long before the government had any mitigations – because I read the reports from China and re-read original SARS research. But the point is – choir members have high risk contacts, and spread efficiently to them – that other people don’t. There is real variety in our social habits that affects efficiency of spread.

        BUT… I suspect that the pattern is already captured in R0 – after all, it is measured in a real population, and that presumably already has the heterogeneity. So unless the heterogeneity changes through the course of the infection (which is hypothesized in the paper I linked), or the population is atypical, the effect is cancelled out. The hypothesized changes require channels of infection that can be “burned out.”

        Thoughts?

      • I forgot to mention:
        Many of these people claiming to model a low HIT, focus on factors that can lower HIT while ignoring factors that can increase HIT. Back in May I pointed out Lewis doing the same thing:

        “Applying the above points to HIT means that one can have a scenario in which HIT is higher than expected because:
        – antibodies are less effective at preventing disease than expected;
        – or vaccination / infection uses non-antibody, memory mechanisms to improve subsequent responses to the pathogen, and these mechanisms are less effective than expected;
        – or the virus mutates to a form previously infected people are not immune to, and that mutated virus begins to make up a larger proportion of the viruses infecting people;
        – or…
        So it’s cherry-picking to just focus on the factors that can make HIT lower than expected, while ignoring the factors that can make it larger.”

        https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/#comment-916999

        Since then, there’s been more evidence on factors that can increase HIT. For example, the evidence on re-infection has grown, showing that people who were once immune to infection are no longer immune. And one should expect more re-infection to occur as more people serorevert in the upcoming months, the virus continues to mutate, etc. It looks like infection-preventing humoral immunity to SARS-CoV-2 is behaving like humoral immunity to seasonal coronaviruses: lasts for about 6 months or more, but then gradually falls below the limits of detection between ~7 to ~18 months.

      • Re: “There is real variety in our social habits that affects efficiency of spread.”

        But as I noted previously, that pattern does not generate anywhere near enough heterogeneity to drive HIT to the low levels of ~17% that contrarians like Lewis claim. We know this because there are numerous populations of substantial size engaging in non-specialized activities with infection rates >40%. That’s what I meant when I said people’s theoretical, hypotheticals about high heterogeneity don’t work in light of what the biological evidence shows.

        Lewis previously tried explaining away an infection rate of ~30% back in May when Joshua pointed them out. But he’s not going to be able to special plead his way out of this ( https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/#comment-916649 ). I already showed a Twitter thread on this, but I’ll list examples below:

        Iquitos, Peru:
        71%
        https://web.archive.org/web/20201102030724/https://www.researchgate.net/publication/343414173_Seroprevalence_of_anti-SARS-CoV-2_antibodies_in_the_city_of_Iquitos_Loreto_Peru

        Dhaka, Bangladesh:
        45% overall, 74% in slums
        https://www.icddrb.org/news-and-events/press-corner/press-releases?id=97&task=view

        Pune, India:
        51% overall, 66% in a subward
        https://www.medrxiv.org/content/10.1101/2020.11.17.20228155v1

        Monteria, Colombia:
        55%
        https://academic.oup.com/ofid/advance-article/doi/10.1093/ofid/ofaa550/5977863

        Karnataka, India:
        47% overall, 54% in urban areas
        https://www.medrxiv.org/content/10.1101/2020.11.02.20224782v1

        Bueno Aires, Argentina (slums):
        53%
        https://www.medrxiv.org/content/10.1101/2020.07.14.20153858v2.full

        Atahualpa, Ecuador:
        48%
        https://www.tandfonline.com/doi/full/10.1080/20477724.2020.1826152

        Maranhão, Brazil (phase 1)
        40% overall, 48% in the Médio region
        “Our results suggest that the herd immunity threshold is not as low as 20%, but at least higher than or equal to around 40%.”
        https://www.medrxiv.org/content/10.1101/2020.08.28.20180463v1
        ( https://www.saude.ma.gov.br/estudos-sorologios-de-infeccao-por-covid-19/ )

        Ischgl, Austria
        42%
        https://www.medrxiv.org/content/10.1101/2020.08.20.20178533v1
        (https://videocast.nih.gov/watch%3D38084, from 40:29 – 42:02 )

        Mumbai, India (3 wards):
        ~40% overall, 56% – 58% in slums
        https://www.medrxiv.org/content/10.1101/2020.08.27.20182741v1
        https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20)30467-8/fulltext
        https://indianexpress.com/article/cities/mumbai/higher-share-in-slums-exposed-to-virus-than-in-societies-mumbai-sero-survey-6527865/

        If we were truly dealing with high heterogeneity, then this shouldn’t happen. Instead you’d expect something like what you see with an STI like HIV, where there are high rates of infection in people who engage in specialized behaviors like certain forms of sex or IV drug use (setting aside exceptions like maternal-fetal transfer, rape, blood transfusions, etc.), while low population-wide infection because of much lower infection rates in people who don’t engage in those behaviors. What we’re instead seeing with SARS-CoV-2 is high population-wide-infection and even higher infection rates in sub-populations, if there’s insufficient public health interventions and behavior changes. Those results are consistent with what Ferguson et al. noted in their March report (which included a herd immunity threshold, with overshoot to ~80% infected), along with other sources on HIT >= 50%:

        “In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic”
        https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/

        “A method is presented for estimating the model parameters from real-world data. It is shown that increase of infections slows down and herd immunity is achieved when symptomatic patients are 4-6% of the population for the European countries we studied, when the total infected fraction is between 50-56%.
        https://arxiv.org/abs/2006.00045

        Herd immunity isn’t dictating how far infections rates fall below a range of 70% – 80%; instead, public health interventions and behavior changes are largely determining that:

        “In summary, there are large differences in patterns of per-capita deaths in different countries that are difficult to reconcile with herd immunity arguments but are easily explained by the timing and stringency of interventions. Seroprevalence studies also provide an independent source of information that is highly consistent with mortality data. The herd immunity argument is therefore at odds with both mortality and seroprevalence data, whereas the intervention argument provides a parsimonious explanation for both.”
        https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289569/

        So we are observing the pattern we’d predict with a higher HIT, without high levels of heterogeneity.

      • I am not saying I agree with Nic, because I don’t. I’m aware of the various places with very high infection rates, such as Manaus, Brazil. I am really talking about theoretical issues, not trying to argue that the HIT for this virus in current populations is much lower than 1 – 1/R0.

        I was mostly asking your thoughts on the idea that R0 already includes the heterogeneity, hence simulations that use heterogeneity but without taking that into account are probably wrong – they are using too low an R0. You could have a whole lot of heterogeneity, but it would not show up infection rates, because the R0 for the same virus, without heterogeneity (in the measured population), would be far higher. The one used to calculate HIT – the measured R0 – is lower than the R0 would be in a homogeneous population. Again, assuming heterogeneity that makes a difference.

        And, the counter to that (all theoretical now) is that perhaps not all the heterogeneity is taken into account by R0.

      • Take a case in which there are differences in susceptibility, to the point that ~50% of the population is immune to infection even without them being infected before. We know that isn’t actually true for SARS-CoV-2, but assume it for the sake of argument. And suppose you infer an R0 of 2 from the observed infection pattern. Then you use the classical homogeneity-based assumption to infer a herd immunity threshold (HIT) of 50%.

        But in reality, the actual R0 is 4, not your inferred R0 of 2, giving you an actual homogeneity-based HIT of 75%. The virus was contagious enough to look like it had an R0 of 2 when its spread was limited by 50% of people being immune. So if you remove the brake of 50% of people being immune, then the real R0 of 4 shows up. Epidemiologists have discussed this before:

        So calculating the actual R0 would involve factoring some things out from your inferred R0. But then there’s the matter of what type of population you’re inferring R0 from. If you infer R0 for an STI from just population a that engages in specialized behaviors (ex: particular sexual practices, IV drug use with dirty needles, etc.), then your homogeneity-based herd immunity calculation will fail when you go population-wide where overall people are less likely to engage in those behaviors.

        However, if you infer R0 from a population-wide sample of people (some of whom engage in those specialized behaviors and some of whom don’t), then your inferred R0 will already include the effect of those differences in behavior, just like your inferred R0 in the previous example included the impact of 50% of people being immune to infection. You then need to hope that as the virus spreads, the population you inferred R0 from is representative of the population the virus is spreading to. You can’t be as sure of that in the case of an outbreak of an STI like HIV, since sexual practices, patterns of IV drug use, etc., can be quite disparate in various parts of the population. So the homogeneity-based assumption is less useful there, in contrast to with a respiratory virus. Similar reasoning applies for other sources of heterogeneity.

        “Spatial heterogeneity in simple deterministic SIR models assessed ecologically
        […]
        To examine the implications of spatial heterogeneity for the management of specific disease types, two different types of infections are simulated in patchy environments: a short-lived respiratory disease and a long-lived sexually transmitted infection.”

        https://www.cambridge.org/core/journals/anziam-journal/article/spatial-heterogeneity-in-simple-deterministic-sir-models-assessed-ecologically/C24D3E55E075B29059AF654BB6D84576

      • “Atomsk’s Sanakan” … “But in reality, the actual R0 is 4, not your inferred R0 of 2, giving you an actual homogeneity-based HIT of 75%. The virus was contagious enough to look like it had an R0 of 2 when its spread was limited by 50% of people being immune. So if you remove the brake of 50% of people being immune, then the real R0 of 4 shows up. Epidemiologists have discussed this before:”

        Thank you. That’s exactly the result I arrived at – same thought experiment. It means that the R0 already takes into account of inhomogeneity.

        Not being in the field, I was not aware that epidemiologists had discussed this before, although it’s hardly surprising. Unfortunately, I was unable to read the paper you referenced on spatial homogeneity – not being in academia, I don’t have access to the walled garden (which ticks me off since virtually everything published in closed journals is paid for by taxpayers).

        Do any of those arguing that the HIT is dramatically lower due to heterogeneity reference any that sort of work?

      • Re: “Unfortunately, I was unable to read the paper you referenced on spatial homogeneity – not being in academia, I don’t have access to the walled garden (which ticks me off since virtually everything published in closed journals is paid for by taxpayers).”

        Try this:

        Click to access spatial_heterogeneity_in_simple_deterministic_sir_models_assessed_ecologically.pdf

        This is something that’s been known for decades. For instance:

        “This effect, called “herd immunity,” can be captured in simple theory describing the impact of vaccination [9]. This simple theory is inadequate for STIs, which have extreme heterogeneity in the risks of acquiring and transmitting infection.”
        https://academic.oup.com/jid/article/191/Supplement_1/S97/936405

        “The concept of herd immunity and the design of community-based immunization programmes
        […]
        Such heterogeneity is directly related to variability in sexual behaviour such as rates of sexual partner acquisition per unit of time.”

        https://www.sciencedirect.com/science/article/pii/0264410X9290327G

        “Modeling heterogeneous mixing in infectious disease dynamics
        […]
        The transmission of sexually transmitted diseases (STDs) often occurs in a very heterogeneous population.”

        https://www.cambridge.org/core/books/models-for-infectious-human-diseases/modeling-heterogeneous-mixing-in-infectious-disease-dynamics/93628D096026492167469DE4F82A35D3

        This is one reason it’s ridiculous when ideologically-motivated non-experts epistemically trespass into the epidemiology/immunology on COVID-19, and think their ‘insights’ are things public health experts never thought of.

        Re: “Do any of those arguing that the HIT is dramatically lower due to heterogeneity reference any that sort of work?”

        The non-experts don’t (ex: Lewis, these engineers: https://www.medrxiv.org/content/10.1101/2020.05.19.20104596v1 ), since they don’t even make it as far as grasping basics like that SARS-CoV-2 cases/day and COVID-19 deaths/day can stop increasing due to factors other than herd immunity. I don’t see the ‘low HIT’ people with expertise citing that research much either, if at all, since the STI comparison undermines their point when it comes to a respiratory pathogen like SARS-CoV-2. Once you recognize what a pathogen outbreak with high heterogeneity actually looks like (ex: the HIV/AIDS pandemic), it becomes obvious that the SARS-CoV-2/COVID-19 pandemic isn’t like that.

        There’s something poetic or fitting about all this. For years, I’ve dealt with vaccine deniers who refused to accept the reality of vaccine-induced herd immunity. But now I’m getting denialism from the other end, with non-experts acting as if non-vaccine-induced herd immunity already arrived when it clearly didn’t. Interestingly, many of those deniers are also denialists on anthropogenic climate change. Crank magnetism is what it is.

  68. IFR data today: global 2.4; UK 3.8; Italy 3.8; Canada 3.7; Sweden 3.5; Australia 3.2; Ireland 2.9; Bosnia 2.9; Brazil 2.8; Spain 2.8 Belgium 2.7, Roumania 2.5 Moldavia 2.3; Bulgaria 2.2; France 2.2. USA (doing not so bad) 2.2
    Scandinavia: Sweden 3.5; Finland 1.9; Denmark 1.2; Norway 1.0; Iceland 0.5.
    China 5.4; Japan 1.6.

  69. Template:covid-19 pandemic data wikipedia

  70. I brought up the behavior aspect with Nic a couple of times. Once related to this article:

    https://www.theatlantic.com/health/archive/2020/07/herd-immunity-coronavirus/614035/

    Never felt like I got a satisfactory response.

    FWIW, I saw this tweet from Gomes.

    She is a well-respected researcher in the field. I nonetheless, I have a hard time accepting what’s going on in Sweden as an expected dance going back and forth over the HIT. And this seems like a huge jump over that line. But unlike me, she knows what she’s talking about.

    • Gomes is much more informed than Lewis. For example, she doesn’t commit his distortion of assuming the herd immunology threshold (HIT) was reached just because cases/day, hospitalizations/day, and COVID-19 deaths/day decreased:

      https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-932643

      However, she’s still wrong in her conclusion that HIT was low. For example, her position on herd immunity predicts that places with more cases during the first wave would have less cases later, since their immunity from the first wave would limit R, or their reproduction number, later on. Thus, more cases overall should limit the occurrence of new cases, meaning plenty of dots in the bottom right of the graph below:

      Obviously, that isn’t what happened. Instead, we see many countries that had less total cases have more new cases now; i.e. top left of the graph. That’s what you’d expect if their testing was much worse in the first wave, causing them to fail to catch many of their early cases.

      We also see many places with lots of total cases have many new cases recently (ex: Spain, Sweden, etc.), and many countries who had less total cases have less new cases recently (top right of the graph, and bottom left of the graph, respectively). That’s the pattern one would predict if factors like competency in public health interventions were what limited cases, not herd immunity. The conditions for a more cases earlier still remain as conditions for more cases later. Presence of those factors during both waves limited both total and recent cases, while absence of those factors in both waves allowed for more total and recent cases:

      So that’s one way Gomes’ position fails in comparison to better explanations. Another problem is that Gomes’ position implies lower IFRs than we observe under higher seroprevalence situations:

      There are other issues with her work. But suffice to say that at this point, informed experts who are paying attention can tell she’s wrong. Yes, her reasoning is more sophisticated and nuanced than Lewis’, as I would expect from someone with her academic background. But she’s still wrong; I could predict she’d be wrong back in May and earlier. Immunology, heterogeneity, etc. just do not work the way Gomes thinks they do.

      Her work has, unfortunately, been picked up largely by right-wing, ideologically-motivated contrarians looking for any excuse to downplay COVID-19 in order to evade policies they dislike. So what would have otherwise been an interesting academic idea that’s quickly recognized to be wrong and not acted on, is instead turned into a dangerous menace to public health that’s defended by uninformed ideologues no matter how many false predictions it makes.

      (with: “Spatial heterogeneity in simple deterministic SIR models assessed ecologically”, section 3.2)

      “Other epidemiologists are also skeptical of the low numbers. Jeffrey Shaman of Columbia University said that 20% herd immunity “is not consistent with other respiratory viruses. It’s not consistent with the flu. So why would it behave differently for one respiratory virus versus another? I don’t get that.””
      https://www.quantamagazine.org/the-tricky-math-of-covid-19-herd-immunity-20200630/

      https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/#comment-917050
      https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/#comment-916999

  71. What is CFR?

  72. OK, I was able to find myself that CFR is a case fatality rate and that is what I was calculating. There is good data for that. I have not seen data based on serological studies needed for IFR. So the IFR figures must be guesswork.

    • In rapidly spreading epidemics such as the current coronavirus pandemic, it is usually expected that a majority of the population will be infected before herd immunity is achieved and the epidemic abates. The estimate of when the threshold for this is reached is usually based on models that assume all individuals in a population are identical. Researchers at the Max Planck Institute for the Physics of Complex Systems in Dresden have used a new model to demonstrate that herd immunity can be achieved at a lower threshold if some individuals are more easily infected than others.

      • That’s part of the heterogeneity supposition. A basic SEIR model (or equivalent) doesn’t account for the various differences in the population – susceptibility, social networks, etc.

        I have an SEIR model that I wrote in late February, and have not put in heterogeneity into it. But, it shows something that a lot of people don’t appreciate: HIT overshoot. I ran a more or less worst case (no NPI’s) and got an overshoot over about 30% – meaning that after HIT was reached, another 30% of the overall total were infected.

        That overshoot is a factor of viral prevalence and R0 (or Rt). If you have a very active epidemic – which you will if you hit HIT without vaccination, and the pathogen has an R0 in the range we see for COVID19 – then a lot of cases happen after that time.

        Another way to see that is to look at the popular curves that were published. When the slope goes from positive to negative is when the HIT is hit (all other things equal). All the area under the curve after that point is infections that happened after “immunity” (if thought about too loosely).

        Note that this can also explain very high levels found in some populations. If there is a really high degree of possible transmission events, Rt can be *greater* than R0, and thus the overshoot can be even larger. If that event is used to estimate R0, the estimate could be too high.

      • Let me add – I’ve seen a number of papers where heterogeneity of one sort or another is tossed in, and the HIT comes down from the homogenous case. I have no way to know whether any of that is valid.

      • meso –

        I can’t really follow all of that, but I saw this article about overshoot from way back

        https://www.google.com/amp/s/www.nytimes.com/2020/05/01/opinion/sunday/coronavirus-herd-immunity.amp.html

        and for all I know, sure, that might explain why Sweden has both a high population infection rate and currently a high attack rate – even after people said they reached a HIT 6 months ago.

        But from my perspective of ignorance, it just seems either nuts or effectively meaningless to say that they reached a HIT six months ago when compared to their Nordic neighbors they have a way higher per capita death rate (and per capita illness rate) even as they currently have a much higher infection rate, hospitalization rate, ICU admission rate, and death rate.

        So if it somehow is true in a technical sense that they reached a HIT six months ago I say “so what?” It’s clear that having reached a HIT six months wouldn’t be a justification for employing a “light touch” in Sweden, let alone in a country like the US which doesn’t have the same structural conditions to make a “light touch” approach work as efficacious as it might be in Sweden. And that is how Nic and many other libertarians were trying to leverage the “herd immunity” and “focused protection” advocacy.

      • Joshua, I think you misunderstood my post.

        I do not think Sweden reached HIT. While the peak of the curve happens at HIT, HIT is not the only way a peak can be hit. NPI’s can cause exactly the same effect, and that’s pretty clearly what happened in Sweden. It is dangerous to look at curves and infer the cause of the shape. One can see a curve that has the shape caused by hitting herd immunity, and then infer that HIT happened, but that’s simply not right. After all, if you lock down a country completely – literally zero contact between people, you will also see a peak shortly thereafter, followed by a sharp drop. But that peak and drop would be due to that intervention, not herd immunity – in fact, not due at all to immunity.

        The heterogeneity modeling suggests that the herd immunity threshold derived as the simple function of R0 is too high. That might be true, but I’m not convinced. I’m going to read that paper and see if they made an error that I believe they did. The simple function says that the fraction of the population needed for herd immunity is 1 – 1/R0, and the heterogeneity folks say it is lower than that.

      • meso –

        Thanks. Yah, I wasn’t really thinking that you thought they’d reached a HIT in Sweden. And yes, it does seem to me that theoretically there could be an “intervention-contingent” HIT that would fluctuate. And it does seem to me that projecting based on homogeneity would inevitably be wrong and likely too high. But on the other hand, I am highly skeptical that people have enough knowledge yet to understand what the real impact of the heterogeneity is…

        And for sure, I think that trying to backwards engineer from something as highly uncertain as the current infection rate to infer the status of herd immunity – as Nic did in the case of Sweden – is just not a very good idea. One might happen to be right when doing so, but the chances are that you missed a whole lot of relevant factors.

        I kept saying to Nic that he was treating uncertainties selectively, and suggesting some of the ways that he had done so. I kept saying that it was way to early in the game to support the confidence with which he was drawing conclusions. I”m not that bright and so I can understand at one level why he basically ignored my criticisms of his reasoning. But that doesn’t justify the clearly flawed processes of his analysis. It’s particularly ironic given that he was posting here when Judith’s main mantra is about uncertainty.

  73. Germans reach the same conclusion as Nic Lewis but the reality in Sweden tells a different story.

  74. I see Sweden’s covid death plot at world of meters today. Their 7 day moving average has been dropping for 7 days now. Late reporting could change this.

    My argument is that not effective herd immunity in Sweden then seems to require another answer for the their second wave not getting traction and fizzling.

    Societies are segmented. Some segments will obtain effective herd immunity first and others later. Their second deaths wave is suggested to be the lagging segments. Not flashing back to the other segments that all ready had effective herd immunity.

    Their second wave as of now lacks sustain. Lacks volume throughput.

  75. Ioannidis’ buds at Stanford put population infection rate at 9.3%, using a sample they argue is nationally representative.

    Figuring that with everyone infected as of today the death toll will be 280 million?

    That puts the IFR at above 0.9%, or some 4-4.5 times higher than John’s estimate. Maybe John should have bothered to try to collect a representative sampling?

  76. Got a good link to share?

    Also, the following just appeared in my mail re: T-cells. An interesting discussion, not directly discussing the impact on surveys: https://www.medpagetoday.com/infectiousdisease/covid19/89777?xid=nl_covidupdate_2020-11-19&eun=g1497256d0r&utm_source=Sailthru&utm_medium=email&utm_campaign=DailyUpdate_111920&utm_term=NL_Gen_Int_Daily_News_Update

  77. It seems that they are adding deaths into Sweden’s numbers. For instance, today’s plot might have deaths added to yesterday’s death number, next week. This sounds bad right? No.

    Sweden’s second wave. 64 deaths per million so far. 1 in 15,000. Make that 640 deaths per million for their second wave. 1 in 1,500.

    That’s not a lot.

    • I have explained this to you multiple times. It’s due to lags in reporting.

      I have given you multiple links.

      You claim that you understand the effect of the lags, but refuse to do so.

      • Ragnaar’s 90/10 example:

        I have 90% of the money and you have 10% of the money today.

        I have 90% of the votes and you have 10% of the votes today.

        I don’t care what some guy in Sweden says about this or how many PhDs he has. Or if the guy in Sweden is a CPA. I have 90% of the money. It is true I thought I had 92% of the money. Then the second wave seemed to grow a bit from later additions. I dismissed that but you didn’t. I now don’t dismiss that.

        I think you’re trying to frame it. I am trying to do that with context. I am contending that their first wave dictates their second wave. That first waves dictate second waves. That deferral comes with future costs.

        I just looked at NY and NJ. There deaths curves are Sweden’s as of now. So whatever NY and NJ is saying is equally wrong. More so. Their second waves are even less than Sweden’s. But argue Sweden will be fine.

        This thing does this is in this situation. These are 3 examples of that. That’s my argument.

      • > That first waves dictate second waves. That deferral comes with future costs.

        You’re just pulling stuff out your a$$ based on what you want to believe. To the extent that the first wave “dictates” anything (which imo it doesn’t) it’s that a big first wave predicts a big 2nd wave.

        You’re still just ignoring the lags and ignoring the illness and still ignoring the economic outcomes we’ve seen and ignoring the sacrifice of heroes.

        And you’re ig doing the effect of a vaccine that would make ALL of Sweden’s potential front-loading of sacrifice completely worthless.

        You never actually deal with any of that. Never.

    • > Sweden’s second wave. 64 deaths per million so far. 1 in 15,000. Make that 640 deaths per million for their second wave. 1 in 1,500.

      The per capita deaths in Sweden are many multiples in the surrounding Nordic countries. How easy it is for you to dismiss the relevance of (unnecessary) deaths of other people’s family members.

      You ignore the impact of illnesses. You ignore the pressures on the healthcare system and healthcare workers.

      And you ignore the impact on the economy. It has been worse in Sweden than in it’s Nordic neighbors. Public health officials in Sweden are currently imploring Swedes to stay home and isolate.

      Remarkable. You have reached self-parody.

    • > The number of Covid-infected people in intensive care beds doubled to 182 over the past fortnight.

      >> Earlier this week, Lofven took what he called the “unprecedented” step of banning public gatherings of more than eight people. From Friday, no sales of alcohol will be permitted after 10 p.m.

      https://www.bloomberg.com/news/articles/2020-11-19/sweden-rejects-face-masks-as-covid-cases-soar-icu-beds-fill-up

      • Yeah, that’s pretty much a cherry-pick I agree. Pretty much falls into the damned lies and statistics category.

        But it is interesting nonetheless.

        > which is somewhat expected considering their latitude.

        >> Most of the northern states are now having their first wave and/or their second wave which is expected based on their latitude.

        Oy. Mute if the “latitude” I sense, eh?

        Say, weren’t you the no 2nd wave fella?

      • Joe - the non epidemiologist

        Josh – again showing his bias

        hugely cherry picked chart
        Starting date for the chart is July
        Omitting the months of Feb, March April may & june thereby omitting the much higher death rates in the NE USA.

        The southern states had their first wave starting in early June which is somewhat expected considering their latitude.
        Most of the northern states are now having their first wave and/or their second wave which is expected based on their latitude.

  78. One thought that occurs to me… I wonder if any of these modeling efforts that focus on heterogeneity captured then clear racial and ethnic disparities in infections and deaths. My guess is that none of them have.

    If so, that should be a red flag – that they don’t know nearly as much about the impact of heterogeneity as they think they do.

  79. White rose Katie Hopkins compares the ever increasing Covid-draconian lockdown measures with the atrocities of Naziism:

  80. As of yesterday, Sweden has not seen a covid deaths breakout. The peak of their second wave was 25 deaths/day using the 7 day average or 9,125/year. Less than 1 in 1000.

    • > The peak of their second wave was 25 deaths/day.

      I’m now convinced you’ll never learn.

      You have no idea what the “peak” of the 2nd wavd “was.”

      I tried. You clearly don’t want to learn.

      • We can agree, ‘Second Wave’ is poorly defined. I often talk about value. You and I place different values on different things. We’re both talking about some data. I suppose I value data that allows me to say something concrete about sticking a fork in this deal. I also value this thing being done or being able to consider it done. Freedom from this thing.

      • No. You’re just wrong to talk of what the “peak” of a 2nd wave “was.”

        That has nothing to do with values.

        Yeah, we prioritize values differently – especially in a specifically politicized context. That is a key issue. Its the real discussion.

        But it doesn’t change that you’re just wrong to talk of what a “peak” of Sweden’s 2nd wave “was.”

      • It could turn out I am wrong about a peak of the 2nd wave. It currently presents as a peak. Data from this week could that. But that’s semantics.

      • The data do not present a peak.

        You have seen the ICU data. Obviously, there is a link between the ICU data and deaths with a lag. You are believing in pixie dust if you think there would be such a dramatic increase in ICU data increasing up to very recently without an increase in deaths going forward.

        There is zero chance you have seen what the “peak” in the 2nd wave “was.” the only way that would be true would be if you were to see a peak in something like ICU admissions and waited a week or two at least.

        I keep telling you this.

      • I will say this… most recent data seems to suggest that the rate of increase in cases and ICU admissions has slowed. And they’ve stepped up interventions including reducing the limit on gatherings from 50 people to 8. It seems that they’ve moderated their policy in accordance with facts on the ground.

  81. Pingback: The Herd Immunity Case – Econophysics2020

  82. What’s been happening is deaths are added later to the second wave. That should be apparent here:

    We can also see the 90/10 line has moved right:

    Since the daily deaths were so low in the range where the line moved right, it’s not that big of a deal.

    So the longer the second wave stays small compared to the first wave, the better Sweden’s future will be. But of course this is not 100%.

    While I have heard cases are running wild, when that happens with limited deaths, something good is happening. The population is resilient to the current situation. Telling them otherwise, seems to have negative value.

  83. This wave doesn’t look at all good to me. It looks like deaths lag, but track cases, as one would expect.

    Full image from 91-divoc.com

    • I agree, this is behaving as every other respiratory infection pandemic before it. In mid-September I predicted on this website that there would likely be a second wave. The early signs were already appearing in the central northern states.

      Problem is lock downs don’t seem to make any meaningful difference beyond those actions that rational people would take regardless. Michigan has been under orders for months yet our second wave is as bad as any. Now obviously we could posit an alternative universe were it was credible to severely punish anyone who violated a srict lock down order and literally trap everyone in there home. It is trivially true that if social connectivity is reduced to nil, then that would stop the spread. In a free society what is possible is not meaningfully effective.

      • > Problem is lock downs don’t seem to make any meaningful difference beyond those actions that rational people would take regardless. Michigan has been under orders for months yet our second wave is as bad as any

        The problem is your logic. You don’t actually know if the current situation in Michigan wouldn’t be worse absent previous interventions, yet you’re sure that you do know.

        Sweden has far worse outcomes than the most comparable countries. They had far worse outcomes early and have far worse outcomes now.

        Is that because the other countries had mandated interventions whereas Sweden relied only on an assumption that people would act “rationally?” I don’t know, actually, but neither do you. And you claim that you know. Why is that?

        What we do know is that the theories that Sweden would have better outcomes (at this point) because of theories about “herd immunity” certainly seem to be falsified.

      • Joe - the non epidemiologist

        Dougbadgero comment – “Problem is lock downs don’t seem to make any meaningful difference beyond those actions that rational people would take regardless. Michigan has been under orders for months yet our second wave is as bad as any. ”

        Josh comment – “The problem is your logic. You don’t actually know if the current situation in Michigan wouldn’t be worse absent previous interventions, yet you’re sure that you do know.”

        Consistent with Doug’s comment, Several countries in Europe are going through a second wave, along with several states in the US such as colorado and Wisconsin, (which both are effectively their first wave) Colorado has had very high compliance with masks and social distancing. Most of the European countries have high compliance with masks and social distancing. The point Doug made is that there seems to very little correlation between the effectiveness of lockdowns and / or compliance with masks/social distancing and the timing of the surges. Doug, my apologies if I missed characterized your comment, but the bottom line is consistent with Doug’s which is that lockdowns’s etc have far less effect than generally perceived by those advocating those actions.

      • “Most of the European countries have high compliance with masks and social distancing. ” – Do you have evidence of that? I’d bet that they have pandemic fatigue, and people are taking certain chances – such as medium sized private gatherings at homes, with more than one household present.

      • Lock down’s don’t work if people don’t take reasonable precautions. Michigan had some very arbitrary lockdowns early on, and that angered a lot of people (reasonably so), and that may have led to low compliance.

        “Rational people” – is a problem, because it depends on motivation. If they don’t care much about what happens to those at high risk, rational low risk people can choose to ignore precautions because they don’t expect to get seriously ill. Also, the whole thing has become unnecessarily political, and that leads people to make decisions (and advocacy) based on tribal (political) identity rather than rationality.

        I see lots of people grasping at every bit of evidence they can to show that, for example, mask wear doesn’t work. They *want* to believe that because the other tribe is pushing mask wear – at least to their perception. And, there’s a lot of misinformation out there. Furthermore, the media is widely, and properly distrusted, because they have become so biased that the mainstream outlets can only be trusted to do one thing: present propaganda that benefits their “tribe.” Unfortunately, this furthers the misinformation, in fact, I think that if the media presents something as a recommendation, too many people, out of their distrust and anger, will instinctively treat it as misinformation.

        There are free societies that are doing far better than the US. Taiwan has never had a lockdown. Australia uses them judiciously, as did New Zealand.South Korea has used lockdowns more judiciously, but they are doing relatively well because their citizenry is in agreement with the measures needed, plus they rolled out massive testing and relatively intrusive contact tracing.

        “Pandemic fatigue” is a real thing and it leads people to make less than rational decisions because they are just fed up.

        BUT… what are they going to do when this time, the hospitals hit overload, and the death rate goes way up? Or when they or a relative needs hospital care for a non-COVID illness and dies instead?

        We may not be able to get people to behave until the carnage intensifies. But that is not something to favor.

        Check out this graph. Then, change “United States” to “Taiwan” to see what happens. With the US on the graph, you can’t even see the detail in the other free country data, because their levels are so low. Note: *free country*.

      • I really wish one could edit comments on this site. See this for the right graph.

  84. Darn – my graph link is to the right site, but not the right graph. See this The site is 91-divoc.com.

  85. Joe - the non epidemiologist

    From Mesocycle – “Check out this graph.”

    Interesting graph – with the exception of the NE US (which got hit hard in March/April) , the change in infection rate seems highly correlated with latitude. Colorado and Wisconsin being high compliance states having nearly the same Infection rate where as the less compliant states in the south are not currently having surges in the infection rate. The southern states had their surge last June/July.

    • Joe - the non epidemiologist

      The west coast of the US seems to be the exception to the latitude correlation.

      The Asian countries all have very low infection rates. This virus seems to be highly infectious. The significant differences in infection rates between caucasian areas/countries cont be completely explained by better compliance, especially considering the much smaller infection rate delta comparing high compliance vs low compliance regions in europe and the US .

      Likely that genetics plays a significant factor – or possible cross immunity prior exposure to other coronaviruses.

    • I think the correlation is more with cold+dry, but it isn’t perfect. I can’t explain the low rates in the far NE.

      A couple of graphs. First – see the map at this link – it’s a heat map of prevalence by Arizona county. With the exception of a couple bordering Mexico (which has a COVID19 crisis right now), the others almost trace out the SW outline of the Colorado Plateau – a high altitude feature that extends into NE and E Arizona. One of the counties (the worst one, as it turns out). But all of those NE and E counties are at higher elevation that the central desert.

      A similar map for the US is here.

      Both of these are from us-covid-tracker.com.

  86. Joe –

    > Likely that genetics plays a significant factor – or possible cross immunity prior exposure to other coronaviruses.

    I’m curious…. There are a ton of qualified researchers and specialists studying the correlates with differential infection and disease severity rates. Have you done a comprehensive survey of what’s out there? Is that how you’ve developed your opinions?

    If not, the least you could do is contact some of those researchers and bring them up to date – so they can benefit from your deep analytical insight as to what is and isn’t likely

    • Joshua: “If not, the least you could do is contact some of those researchers and bring them up to date – so they can benefit from your deep analytical insight as to what is and isn’t likely”

      We have mostly had a civilized discussion here. Why not keep it that way? Why attack speculation that is clearly speculation, but is interesting?

      I know of nobody ruling out genetics, for example. It could be that they have, but in that case, why not cite it rather than using that mocking attack? Are you implying that only experts should comment?

      • meso –

        > Why attack speculation that is clearly speculation, but is interesting?

        That’s fair enough. Attacking speculation isn’t defensible. I just find it amusing when people who actually have not studied the material and have zero expertise are stating what is and isn’t “likely” in these complex matters. But it’s true that there’s zero harm likely to arise from Joe over-evaluating his own insight so making fun of him is gratuitous.

        > Are you implying that only experts should comment?

        No. Especially as a non-expert myself.

        But I do think that people who have zero expertise and who haven’t even comprehensively studied the research that’s out there, should be circumspect and respect uncertainty. Determining who’s an “expert” is something that’s somewhat subjective, and of course there’s no reason why non-experts are obliged to be silent, but there’s also a problem, specifically with COVID but with many other similar issues, where people with zero expertise and an over-developed sense of their own insight casually dismiss the value of expert analysis and instead add to the tsunami of ignorance and misinformation that’s out there. IMO, that problem has had real world negative impact on our society via a vis COVID.

        To the extent that I display a similar habit of getting out in front of my own expertise and insight, and don’t appropriately acknowledge uncertainty, it’s more than appropriate for people to call me on it. In fact, I want them to. I won’t be intimidated but I will think about the feedback (and evaluate it in the appropriate context). I think Joe’s able to do that as well.

        In this particular post from Nic we have these issues in relief. We have a non-expert contributing his analysis in such a way as to advocate for a particular policy outcome that he favors (while acting like he isn’t a policy advocate – but that’s another issue). As a result, we arguably have had more people ignorantly favoring a “herd immunity” strategy when pursuing such a policy may well result in unnecessary illness and death on a significant scale.

        Do you think it’s inappropriate in such a context to highlight that people who have no real expertise are placing themselves in a position to materially affect public opinion with a deliterious effect? Do you think we should not point out for consideration that they are opining on issues and contradicting the evaluation of experts even though they have not comprehensively studied the literature?

        Their lack of expertise isn’t dispositive as to the correctness of their opinions, but I think it is relevant for people who aren’t experts themselves to use evaluating expertise when considering the probabilities of conflicting analyses.

      • This caused a splash a while back – although I haven’t run across anything about it since it first came out. I assume you’ve seen it?

        https://www.nature.com/articles/s41586-020-2818-3

      • Re: the Neanderthal link. I’d just seen a passing reference, so thank you. It’s very interesting!

        Given the fact that Neanderthal genes vary in prevalence, or are missing altogether, depending on one’s racial group. I have read that death rates are high in some special indigenous groups that would have low or zero Neanderthal genetic complement: Navajo’s here in Arizona, and some native populations in Brazil. But, those could also be affected by behavioral factors, co-morbidities (common in Navajo’s, I think, but I don’t know about isolated Brazilian indigenous peoples), and of course sanitation and health system quality.

        An interesting example of genetic susceptibility happens here in Arizona with the Pima tribe. Pima’s in the US have the highest rate of type II diabetes of any population known (not true of Pima’s in Mexico). A friend did her OB residency partly at the Indian Hospital in order to work with diabetic pregnant women.

        It is hypothesized that this trait resulted from periods of past famine that strongly favored a “thrifty gene” which could make the best use of sugars, and that this, in higher carbohydrate diets available now, leads to diabetes.

      • And keep in mind, meso, that we had people all over these pages confidently asserting that rhe epidemic in the US was over months ago, that the surge in infections in the summer wouldn’t result in a surge in deaths because it was only an increase in asymptomatic cases and cases among young people, that there wouldn’t be second waves in areas that were hit hard in the first wave, that Sweden reached a herd immunity threshold 6 months ago, that we wouldn’t get a vaccine rolled out before the country reached herd immunity through infections, that masks don’t have any benefit, and actually that masks spread the virus fastee than would happen otherwise.

        Is there any point at which you think it IS appropriate to point out that the people confidently offering such opinions actually have no relevant expertise?

      • Joshua, thank you.

        To clarify – my reason for the comment was your attack on Joe, who was not exhibiting the kind of certainty Nic does, nor was he speculating about anything nearly as important.

        I have attacked a lot of people in comment sections on the topic of COVID19, when they have used strong certainty to spread misinformation. Since I’m a conservative, I am often disagreeing with people on my side of the spectrum, since those are the comment sections I’m most likely to end up in.

        As one at high risk who has thus been “locked down” with my wife since the start of March, I have little patience with those who assert confidently that masks don’t work, or that COVID19 is a leftist plot, or that lockdowns don’t work (even if I disagree about a lockdown policy in some cases). Thus I get emotional.

        And I go overboard at time. When someone pisses me off, it’s hard to respond in an appropriate tone, but that’s an excuse for me, not a valid reason.

        But on the other hand, the engineer in me and also the fact that I’ve been following emergent disease outbreaks for 25 years or so, leads me to be very interested in all of this out of technical curiosity. I just wish we were dealing with a disease of C. elegans rather than Homo sapiens.

      • meso –

        Related to the questions of when in-expert promotion of their views is problematic. One pivot point is when they start monetizing the misinformation.

  87. How long until Nic buries “herd immunity” in Sweden?

  88. This Ivor Cummins character is a real niece of work. Asserted that the pandemic was over in June in the US. One of those “casedemic” nutbars.

    • Joshua – yeah, if they are profiting from it *and* don’t believe it, that’s evil. But some firmly hold those beliefs, and also have for-profit media operations. I’d say that it would be a lot better if they did more research.

      As I’ve pointed out before, the complete politicization of the mainstream media, to a degree unprecedented in my lifetime, has destroyed a lot of trust, and that lack of trust bleeds over to people outside the media. Plus, some areas of science have been politicized, and also too many scientists imagine that their expertise in their field makes them experts to be listened to elsewhere. All of this are contributing factors to the conspiracy theories and lack of trust in science. I believe that Trump, not trained in science, also falls prey to that, plus the sustained vicious attacks on him have provoked reaction to the attacks. And, Trump is an amplifier – when he’s wrong, more peole will end up wrong, when he’s right, same is true.

      Then add in the fact that most people who comment do not have a science background and also don’t understand how science works – which BTW applies to people other than these COVID resisters. “Believe the science” is a nice slogan, but it’s usually used in a political context.

      Plus, a lot of important information has not come from science, but rather from people informed in the sciences – for example, epidemiologists who have seen these sorts of things before. In a fast moving situation, modern science moves too slowly – RCT’s, peer review, etc take too long to provide the information, even though those – when stretched out over a few years (time for refutation, confirmation experiments) tend to be the most accurate.

      Put another way, while medical practitioners (and engineers, too), are trained in science, most of their work is not doing science, it is applying results gained from science.

      None of this means I condone those spreading misinformation. I’m just looking at causes.

  89. meso –

    >But some firmly hold those beliefs, and also have for-profit media operations.

    So here we have slippery slopes running in either direction. We can’t just shut down people who write analyses we think might be mistaken just because someone might disagree with it. But on the other hand we see that people who don’t have a sophisticated take and who lack any relevant experience or expertise will publish nonsense that has real world deliterious consequences. If they believe the nonsense they’re promoting (primarily because it fits with their ideological preferences) , does that just mean it’s OK?

    This is a predicament that roils our society today.. Perhaps it always did. Perhaps social makes it worse. Or maybe it’s just really an age-old problem. But it’s a real problem. Someone like Cummins has a huge following and the nonsense he’s putting out there may cost many lives. I don’t know the solution. Just shutting people down isn’t viable but the simple explanation that he might believe the nonsense, as a license to spread harmful nonsense, seems inadequate as well.

    > As I’ve pointed out before, the complete politicization of the mainstream media, to a degree unprecedented in my lifetime,

    What metric are you using to measure this trend? We can certainly say that there are fewer resources devoted to investigative journalism but the media has always been massively politicized – consider William Randolph Hearst, and politicization of the media has been a complaint from partisans since day one. And consider that the internet supplies an infinite number of sources for information.

    > has destroyed a lot of trust, and that lack of trust bleeds over to people outside the media.

    Many measures of overall trust in scientists have been largely stable for a pretty long time – even if within the overall stable trend there have been some offsetting shifts (rightwingers towards the far right side of the spectrum have shown a marginal movement from being the most trusting to being less trusting as lefties have moved a bit towards more trusting).

    > All of this are contributing factors to the conspiracy theories and lack of trust in science.

    This is a commonly promoted explanation – but I would argue that there is little supporting evidence for that causality and it’s questionable anyway because of its political convenience for a certain ideological alignment. I don’t think that the explanation that it’s scientists’ fault that some people believe in conspiracies holds water.

    > I believe that Trump, not trained in science, also falls prey to that,

    I disagree. I think that Trump *exploits* that phenomenon cynically. He has had an explicit strategy of levering disinformation for decades. He inherited it from people like Roy Cohn and Roger Stone.

    >plus the sustained vicious attacks on him have provoked reaction to the attacks.

    Again, I don’t agree with your mechanism of cauality or your locus of the origin. I don’t doubt that some of Trump’s actions are *reactions* but many of the attacks against him are reactions to what he does. It’s always funny to me that his supporters simultaneously claim he’s a master of media manipulation and a victim of unfair attacks. When is Trump held accountable for his actions? Isn’t he an adult with agency, as the most powerful person in the world?

    > “Believe the science” is a nice slogan, but it’s usually used in a political context.

    I agree. But on the other hand there IS a problem where people with little relevant knowledge or expertise dismiss the work of scientists because they don’t like the policy implications of the scientists’ work or because they over-evaluate their own analytical abilities.

    • Joshua- like usual, I appreciate your thoughts.

      >?I don’t know the solution. Just shutting people down isn’t viable but the simple explanation that he might believe the nonsense, as a license to spread harmful nonsense, seems inadequate as well.

      If we had a well functioning media, this might be better. But our country was intentionally constructed to grant a license to spread harmful nonsense, because the alternative was viewed as far more dangerous. I agree with that, even as I dislike the fact that people are doing it.


      >..the media has always been massively politicized – consider William Randolph Hearst, and politicization of the media has been a complaint from partisans since day one. And consider that the internet supplies an infinite number of sources for information.

      In the past, the media was not as uniform in its bias. In a city, the mainstream media was newspapers, and there were several, often named for their political position. That created an important diversity. On the other hand, if you go back to revolutionary times, I think it was in some way like the modern Internet – lots of people were printing pamphlets or broadsheets or whatever – but I’m not well informed about that.

      I don’t think the media can be objective, but I do believe that in the last 4 years especially, they have abandoned even an attempt at it. When you believe the other side is not just wrong, but very evil and dangerous, it becomes easy for a partisan reporter to justify intentional bias. And, Trump’s manner just drives people, especially reporters, nuts – conservatives call it “Trump Derangement Syndrome.” But, it is real, and it is an unfortunate side effect of Trump’s personality.

      Plus, the media now, unlike the old days, is “professional” – which means having J-school degrees where they got indoctrinated, and their own echo chambers. And, many went straight from school to work as reporters, never having much “real world” experience. In the more distant past, reporters were just people who found jobs at newspapers. Frankly, I wish that were still true. BTW, my brother, who holds a couple of degrees in journalism, agrees with that.

      The Internet is indeed how conservatives “route around” the misinformation from the mainstream media. But, the Internet ecology has not yet developed enough ways for people to judge which *alternative* sources are trustworthy, or at least, worth reading, and which are just cranks or opportunists. One aggregation site that I really like (Instapundit) has gotten too tribal on COVID for my liking, which is sad. But, I still go to the site a lot for its links, I just often leave comments about what they are saying.

      
>> has destroyed a lot of trust, and that lack of trust bleeds over to people outside the media.
      
>Many measures of overall trust in scientists have been largely stable for a pretty long time

      Until…. it impinges on tribal issues. Then, in our sharply divided, tribal society of today, people let their tribal instincts override their rational instincts. And, since many are distrustful of “experts” (for good reason IMO in many domains), when true experts show up, too many people aren’t careful or knowledgeable enough to recognize that these are worth listening to. I can’t tell you how many times I have gone after Fauci bashers in comments sections, for example. I read Fauci is a classic, nerdy scientist, and I respect him.

      As an aside, as one gets into social measures, sociology, economics, anthropology, political science and psychology are weak – not because they are evil, but because the subjects are very, very difficult to study scientifically – too many variable, and humans in the middle. And, since social scientists are virtually all on the left (that *has* been measured – for example, party affiliation), any conclusion about “right-wingers” or whatever is suspect. I’ve seen a number of studies claiming various negative qualities being possessed mostly by people on the right, but when I read the studies, I realized they were dreck.

      But back to trust… there is a general social trust – high trust societies, low trust societies – but that isn’t the only measure. Americans seem to still be relatively high trust in that regard, fortunately.

      But, trust in institutions has gone way down on the right, because too many institutions have become untrustworthy. And that lack of trust in, say, the mainstream media, is what I’m referring to regarding bleed-over into what should be non-polarized issues such as COVID19 response. I see a mirror lack of trust on the left – for example, anything from the Trump administration isn’t just suspect, but must be a lie.

      So when you see me in the COVID19 discussions, you are seeing a conservative who is not sticking with a “tribal” response, but rather who is sticking to his engineering viewpoint. I have seen the same tribal response from the left, on this issue. It just happens that COVID19 mandates are more inline with the sort of thing progressives favor: experts decide, citizens obey. I truly believe that if Trump were advocating some policies, many on the left would automatically reject them. It’s become very tribal. I wish we could temporarily turn Americans into east Asians – then they would comply – see COVID19 response there. But we are not.

      
>> All of this are contributing factors to the conspiracy theories and lack of trust in science.
      
>This is a commonly promoted explanation – but I would argue that there is little supporting evidence for that causality and it’s questionable anyway because of its political convenience for a certain ideological alignment. I don’t think that the explanation that it’s scientists’ fault that some people believe in conspiracies holds water.

      You misunderstand. I am saying the lack of trust in institutions such as the media bleeds over. It isn’t the scientists’ fault. As for “supporting evidence” – this isn’t something that can be rigorously studied – at least not at this juncture. We are talking about social groups and their beliefs.
 But, having argued with a bunch of people on the right about this – you are hearing the conclusions I draw from that.

      >> “Believe the science” is a nice slogan, but it’s usually used in a political context.
      
>I agree. But on the other hand there IS a problem where people with little relevant knowledge or expertise dismiss the work of scientists because they don’t like the policy implications of the scientists’ work or because they over-evaluate their own analytical abilities.

      I agree.



  90. What do we see?

    Some see a problem greater than the first wave.

    Since October 17th which might be the beginning of the second wave, about 780 people have died in Sweden. Or about 1 in 12,500.

    • We see someone who is pretending to be incapable of understanding condition al probability.

      Or who actually is incapable of such.

      I’ve explained to you many times why it is fallacious to ignore the tends of cases, hospitalizatons, and ICU admissions, in relation to deaths – with also considering lags in reporting and recording deaths. And I’ve also explained many tjmes why ignoring illness and only focusing on death is wilful blindness.

      Your behavior is fascinating.

      • “The European Infection Control Agency ECDC now estimates the number of COVID deaths in Sweden will peak between 100 and 140 per day in December…”
        100 per day is a little greater than the peak rate during their first wave. In the above plots that would be a steeper sloper than the worst of it during their first wave. Since most people agree with you, what do you think your average Swede is doing right now? Whatever numbers you use, you are not using enough of them in the most efficient way. And the same goes with any authority you can cite. This thing will do what it does, the people it impacts will do what they do. Then if the virus can adapt to do what the people do, it will. Just because someone is some place else, that doesn’t mean they’re wrong.

    • > Since October 17th which might be the beginning of the second wave, about 780 people have died in Sweden

      If that 780, how many have been recorded as taking place since Nov. 1?

      About 682.

      And in the next couple of weeks that 680 recorded as having nmdied between Nov. 1 and Nov. 28 will increase significantly as the recording is updated.

      So you really not understand that? Or are you just ignoring it?

      So easy for you to dismiss the sacrifice and illness and deaths of people you don’t know as long as you don’t have to make any sacrifice, isn’t it?

      The people of Sweden are abandoning you.soon all you’ll have left are the fake libertarians.

      • Joe - the non epidemiologist

        the website 91-divoc.com shows the daily infection rate in sweden to be very comparable to the rest of Europe.

        the IFR rate, normalized for 100k population, shows Sweden to be one of the lowest in Europe.

        In Summary – Most all of Europe is currently experiencing a second wave and Sweden is about average of the rest of Europe for the daily infection rate and much better than the rest of Europe for the fatality rate.

      • Joe writes: “the IFR rate, normalized for 100k population, shows Sweden to be one of the lowest in Europe.”

        Best to compare similar countries:

        Total deaths per 100k:

        Sweden: 64
        Denmark: 14
        Finland: 7
        Norway: 6

        Looks like a roaring success for Sweden’s strategy!

      • Joe –

        So if we ignore that you steadfastly ignore the per capita hospitalizaton, ICU admission, and death rates in the most comparable countries to Sweden, what we would be left with at best is that the “herd immunity in Sweden” 6 months ago argument is falsified.

        And at best, if we ignore the hospitalization, ICU admission, and death rates in the most comparable countries as you steadfastly do, we see that Sweden’s outcomes from the pandemic are roughly on par with many countries that have very few of the structural advantages that Sweden has – such as the ability for people to have paid leave from work, and the low rate of people per household, and the low population density, and the low # multi-generational households, higher standard of living, the better baseline health (i.e., fewer comorbidities), etc.

        And we see that as of yet there’s no sign that Sweden has gained any economic advantages from their policies, as many in the “Yay herd immunity” crowd have expected to happen.

        And we see that despite their best efforts, Sweden is certainly not a model for “focused protection” as even now they are seeing infections and spread among the most vulnerable members of the Swedish county.

        Perhaps all of those factors are the reasons why Sweden had begin to mandate interventions more like the manner of many other European countries?

        And Joe, tell me, have you rethought your theories about how there would be no 2nd wave? If anything, it seems that the countries that has the largest 1rst waves are experiencing the worst 2nd waves.

        Have you ever heard of apophenia?

        Anyway, we are seeing large spikes of infections in other Nordic countries as well, and we should expect corresponding spikes in deaths after a lag. Those other countries will never reach the levels of disease and death Sweden has seen – particularly since vaccines seem to be coming on line. But that is enough of a reason for people to avoid the temptation towards looking at short term trends in graphs and fitting analyses about very complex social and medical phenomena to those graphs so as to conform to their ideological predilictions.

    • What is your point? It’s pretty clear that deaths are rising in Sweden – when you take into account that the graph does not include many recent deaths as they have not been reported. In other words, the graph is showing deaths by date of death, not report.

      • We agree on what you said about reporting. My point is their second wave so far is about 1 in 12,500.
        Maybe my point is this: We can see things even if we don’t do or can’t do math. What do you see in the plots? Some people see negative things and want to make a call to acton from the authorities.

  91. Hospitalizations in Sweden now at 90% of the spring peak.

    Likely to result in a lower % of deaths per hospitalization than in the spring. But no reason to assume the hospitalizations won’t go up from here. And it certainly sea to blow the “herd immunity” six months ago theorizing out of the water.

    Where’s Nic?

    • Sweden now has amongst the highest case loads in the world. Only the Balkan countries seem appreciably higher.

      Deaths are following behind as would be expected.

      The contrast with the other Nordics is quite remarkable.

  92. Sweden has had around 1200 deaths in its second wave or 120 per million, or 1 in 8333. Median age you can figure it’s not low.

    Sweden has done better than the United States and 23 other countries and it’s likely they’ve done better than your state.

    No one knows why this is. There’s a good chance it’s not policy as policy is not well correlated with deaths.

    Perhaps you have a reason for saying how terrible it is in Sweden and telling them how they should live their lives. That they don’t have enough government control. Or they’re just stupid. If you have the answers, let’s have them. And where were you 5 months ago applying your wisdom?

    What was the point of schooling Lewis when you could’ve done something to make things better? I’ll tell you two things. Lewis isn’t the problem and neither is Sweden. It doesn’t matter how many times you hang them. Your rhetorical gun is empty but you keep pulling the trigger. Sweden doesn’t care what you think.

    If people like you do not populate Sweden, they’ll be fine. Life has risks. That can be acknowledged or denied. Sometimes nature is bigger than governments and scolding nannies. Take climate change for instance. We solved that one didn’t we by telling other people what to do and pointing out people we knew were wrong.

    You can tell people they’re wrong all day long. What good does that do? You know the answer.

  93. Sweden’s second wave is now at roughly 17% of their total deaths:

    This can be compared with when they were at about 10% of total deaths:

    • Yes – Sweden did a remarkable job of killing off the vulnerable in the early phases.

      But note that Sweden has now instigated significant mitigation mandates. They gave up on their insane herd-immuniity-by-infection quest.

      Sweden looks pretty awful compared to Finland – see image (if I can get it to work).

      [url=https://ibb.co/2n1KHMY][img]https://i.ibb.co/dWwKxpJ/91-DIVOC-countries-normalized-Sweden.jpg[/img][/url]

      • Yes Sweden killed of it’s vulnerable. Even after having done so, they’ve done better than the U.S. Meaning since they are stupid and we are so smart, we have more deaths per million than they do. Meaning intelligence and being the leader of the world doesn’t matter. We can see who has the current problem. And it’s the U.S. by a factor of 4 versus Sweden. We are 4 times worse off than they are this week and last week. They are smarter than us but dumber than Finland. Which means, they are smarter than us. Finland doesn’t have anything to do with it. They are a stooge. Look at us. Don’t look at Finland.

      • ” We can see who has the current problem. And it’s the U.S. by a factor of 4 versus Sweden. We are 4 times worse off than they are this week and last week. They are smarter than us but dumber than Finland. Which means, they are smarter than us. Finland doesn’t have anything to do with it. They are a stooge. Look at us. Don’t look at Finland.”

        So you choose to compare a dramatically different country (the US) rather than compare Sweden to its similar neighbors. That’s dishonest and inappropriate.

        If Sweden had followed the policies of the US, it would probably have done better than Sweden actually did. Sweden enjoys tremendous advantages demographically over the US in this regard, plus its wasn’t the heart of travel early in the epidemic, so it didn’t get seeded with such a high level of infection. It also has a populous that follows government recommendations when they are not mandates. Or, it did, until COVID19 fatigue set in. Sweden now limits gatherings to only 8 people, for example. That’s quite strict. And it’s the first time they’ve done it, which is just dumb.

      • > Even after having done so, they’ve done better than the U.S.

        Remarkably consistent in ignoring relevant factors. There are tons o’ reasons to EXPECT Sweden to do better than the US, in spite of the enormous resources that the US could have brought to bear if we’d had competent and responsible leadership.

        BTW, any comments about this, as a “libertarian” doncha know…:

        https://www.washingtonpost.com/nation/2020/12/09/florida-republican-resigns-raid/

        https://www.theverge.com/2020/12/9/22166012/florida-raid-rebekah-jones-covid-19-data-dashboard

      • BTW –

        They’re working in the legislature to figure out ways to make businesses shut down.

        Oh, and this,

        -snip-

        The head of the health service in Sweden’s capital Stockholm has pleaded for help from the government as the city’s hospitals fill with COVID-19 patients amid a spiralling new wave of infections.

        -snip-

        Please go ahead and scoff at what this means for other people’s lives. Doesn’t affect you, right?

        https://www.businessinsider.com/sweden-coronavirus-surge-alarm-stockholm-hospitals-herd-immunity-strategy-2020-12

      • Joe - the non epidemiologist

        Joshua’s comment – “in spite of the enormous resources that the US could have brought to bear if we’d had competent and responsible leadership.”

        You mean competent leadership like Coumo?

        Or the outstanding leadership in MN with Waltz or the superior leadership in Europe.

        Seems when you acccount for the extremely competent leadership vs the incompetent leadership, the difference the quality of the leadership is only a very minor factor compared to mother nature. – With the exception of Coumo’s screw up.

      • > You mean competent leadership like Coumo?

        I love the “Mommy, they did it toooooo” brand of thinking.

        Cuomo. Made mistakes. Everyone does. What matters most is the degree of accountability for mistakes once made. That’s the way to learn and move forward. Cuomo hasn’t been great in that regard either. Still, the insistence by partisanship-driven observers to defend federal failures by pointing to Cuomo is mostly poirly reasoned.

        > Seems when you acccount for the extremely competent leadership vs the incompetent leadership, the difference the quality of the leadership is only a very minor factor compared to mother nature.

        Within a partisanship-driven world view, no doubt. In the real world leadership has made enormous differences, on top of the structural realities that clearly influence and constrain the potential outcomes.

        > – With the exception of Coumo’s screw up.

        If it makes you feel better about the federal failures by inflating and then focusing on the mistakes Cuomo made, have at it. Given your track record, I would certainly expect nothing else.

      • Joe - the non epidemiologist

        Joshua’s comment – “In the real world leadership has made enormous differences, on top of the structural realities that clearly influence and constrain the potential outcomes.”

        Really ? Waltz’s leadership in MN with the lockdowns along with Colorado’s leadership is vastly superior to the leadership (as you would define leadership) in many other states such as MT, ID, NE, ND, SD, yet the results in those states are remarkably similar to those states with superior leadership.

        You seem unable to comprehend the delta in results between regions with competent leadership vs abysmal leadership is strikingly small.

      • Joe –

        > Waltz’s leadership in MN with the lockdowns along with Colorado’s leadership is vastly superior to the leadership (as you would define leadership) in many other states such as MT, ID, NE, ND, SD, yet the results in those states are remarkably similar to those states with superior leadership.

        (1). That’s not what I said.

        (2) You have demonstrated many times that you don’t understand how to assess causality in the context of the pandemic. And this comment is just another example.

        > You seem unable to comprehend the delta in results between regions with competent leadership vs abysmal leadership is strikingly small.

        Related to (2), you should know that by comparing regions that are highly dissimilar in many respects, you can’t isolate the impact of leadership simply by comparing relative outcome measures, and in particular along only one axis – of you don’t control vod confounding variables.

      • “So you choose to compare a dramatically different country (the US) rather than compare Sweden to its similar neighbors. That’s dishonest and inappropriate.”

        You have to do more than claim they are dramatically different. Nordic is a category that is arbitrary at this point. Where is any research defining what similar versus different countries is? I doubt there is any. This is group A of countries for comparison and these are groups B-H. Here is why this group should not be compared to other groups.

        So you claim the categories. That’s nice.

        What we do know is the U.S. has done worse than Sweden and the U.S is in worse shape today. But categories you say. That’s not what the data says. You get to throw out the data because of categories.

        When Sweden does better than us, we get to criticize it. Sweden is not our husband and we don’t get to tell it to be better. To get a better job when we work at the Seven-Eleven. Sweden is not our child. And we didn’t spend money to send it to college. Sweden is all grown up now and owns a nicer house than we do.

  94. Compared to Finland, Sweden looks pretty bad.

    • Compared to all the Nordics.

      Looks like the increase in ICU admissions rate is slowing even if the ICU admissions isn’t dropping. That could be a hopeful sign. Deaths a few weeks out may start to drop.

      Of course, the “herd immunity” crowd is attributing that to “herd immunity” or “saturation” even though a place like Belgium has a higher per capita case rate (dont know about actual infection rate) and a PFR of 0.15% compares to the (current) PFR of 0.071% in Sweden.

      And of course they ignore the public policy change and public health messaging as a lite risk influence.

      They seem to never learn.

      • Another thing that tends to be ignored by both “sides” is voluntary action taken independent of either mandates or even messaging. I made that mistake early on in my analysis.

        BTW, I tried to post a link to a graph showing just Finland and Sweden, but it doesn’t work.

        Do you know how to post images in these WordPress comments? Some people are able to do it.

  95. Yes, the variable of “compliance” is so basic for assessing interventions, and varying across contexts, yet people think they know what they’re talking about without information on that factor. Very frustrating.

    Would need to know more about what happened when it didn’t post. But there are certainly people who now more about posting graphics than I.

  96. Suggestion that “herd immunity” might be slowing deaths in Lombardy.

    https://www.economist.com/graphic-detail/2020/10/31/italian-towns-hit-hardest-by-covid-19-are-doing-better-now

    Doesn’t bode well for Stockholm, however, as it seems to be associated with a PFR of @ 0.5%, and it’s not like people just stop dying even at that point.

    .

    • If behavior is held constant, herd immunity reduces the rate of growth of the epidemic (and thus deaths), from the very start. But it has little effect for awhile. You can ignore it and treat the growth as exponential for awhile, even though in the strict mathematical sense it is near exponential but not exact. As immunity increases, it diverges.

      More precisely, the R value declines as the percentage of susceptible in the population declines – in a per linear relationship: Rt = R0*Nsus/Npop,

      Of course, behavior isn’t held constant, making it a lot harder to tell what is causing any effect here.

      • meso –

        Sure.

        The general use of the term “herd immunity” in the public discourse in the context of COVID often seems vague and subjective/arbitrary to me – to the point where it doesn’t seem terribly useful to me.

        That’s why we see the “herd immunity” crowd keep making the same mistakes over and over regarding the trajectory of the pandemic.

      • Yes, the term gets misused – but what I’ve seen is people who seek to redefine it, not people ignorant of the standard meaning.

        Plus, of course. most people probably think it’s a magic number – hit that, and nobody else gets sick.

        And I probably should have said “immunity reduces the rate…” rather than “herd immunity.” That was incorrect – immunity in the herd yes, but “herd immunity” means something more specific.

      • meso –

        > but what I’ve seen is people who seek to redefine it, not people ignorant of the standard meaning.

        I dunno. That seems suggestive to me impugning motive, which should be avoided, imo. So maybe some combo of those two choices.

        IMO, people tend look at complex terms that they lack the background knowledge to fully understand, and assume they understand a definition and that the correct definition lines up with their ideological predisposition.

        > Plus, of course. most people probably think it’s a magic number – hit that, and nobody else gets sick.

        That certainly seems to be what a lot of people think. But based on how the public discourse has gone I can certainly understand why people think that. I only really understood differently after reading a Nytimes article about “overshoot.”

        > And I probably should have said “immunity reduces the rate…” rather than “herd immunity.” That was incorrect – immunity in the herd yes, but “herd immunity” means

        But see, it’s only with humility of knowimg that you have to work hard at being specific that such an understanding develops. It’s easy for people to write something like your original wording (you knew what you meant to say but only after rereading realized that you didn’t quite say it), and then for there to be a ripple effect where people read something less than precise written and then misunderstand but think they understand.

        Of course, there are hucksters out there who are deliberately misleading and a whole lot of people who are so motivated by an agenda they lose interest in being specific or lose openness to holding themselves to account for less than perfect clarity.

      • “Of course, there are hucksters out there who are deliberately misleading”

        You said I was impugning motive. Yes, I was, as are you.

    • Re: “Suggestion that “herd immunity” might be slowing deaths in Lombardy.”

      To state what you and I know both know (but Nic Lewis likely still doesn’t): that isn’t herd immunity, since they aren’t under the baseline conditions of R0. Or in other words: there are still additional public health interventions and changes in behavior that they have now, that they wouldn’t have had this time last year in the absence of the pandemic.

      So what we’re dealing with here is population immunity, where some non-zero proportion of people immune to infection helps slow the spread of the virus (i.e. limits R), as opposed to herd immunity, where the proportion of immune people is sufficient to keep R below 1 (and thus keep infections/day from increasing) even under baseline conditions. The article you cited tacitly admits this:

      “Social distancing has also slowed the virus. According to Google, Lombards moved around 24% less in July than in January, the steepest drop in Italy. But this decline has been similar in all of Lombardy. That leaves immunity as the best explanation for differences in case counts within the region.
      These data do not prove the case for seeking herd immunity.”

      https://archive.is/5TaND#selection-3767.0-3771.59

      Bergamo’s ~24% infection rate looks impressively high and promising:

      “Interestingly, the IFR in the Bergamo province – sadly known to have been the epicenter of Europe – was 1.2%, with a seroprevalence of 24%”
      https://www.tandfonline.com/doi/full/10.1080/20477724.2020.1827617

      Until you recognize that its large IFR with a high seroprevalence conflicts with Gomes et al.’s claims on a low herd immunity threshold (unless one engages in the special pleading by assuming HIT is high on a city level, but conveniently becomes much lower on a country-level):

      “The estimate of the herd immunity threshold depends on the value specified for the infection fatality ratio (IFR): a value of 0.3% for the IFR gives 15% for the average herd immunity threshold.”
      https://www.medrxiv.org/content/10.1101/2020.09.26.20202267v1

      And Bergamo looks even less promising when you compare it to other parts of the word that have infection rates of over 40%, or even over 70%. Some examples:

      https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-933276

      This illustrates how many more people the virus can infect if public health interventions and changes in behavior are reversed; i.e. if you get back closer to the baseline conditions of R0. That ties into one of the dangers of conflating population immunity with herd immunity, as I previously discussed ( https://judithcurry.com/2020/10/14/t-cell-cross-reactivity-and-the-herd-immunity-threshold/#comment-932643 ):

      If people ease up too much on changes in behavior and public health interventions because they’ve been told that herd immunity protects them (when they’ve actually only have some population immunity), then R will spike again above 1 again, leading to an increase in infections/day, and likely then increasing hospitalizations/day, leading to increasing deaths/day. It’s tantamount to telling people that they don’t need to:
      – keep wearing masks
      – avoid face-to-face meetings with nursing home residents
      – avoid large indoor concerts (including if they’re elderly people),
      or any of the other things that differ from their lives at baseline, in order to keep infections/day from increasing. This is even worse than the denialism of mask efficacy.

      That’s one reason why Nic Lewis’ (among other right-wingers’) conflation of population immunity with herd immunity was so reckless. I’m not sure how exactly much damage he’s done to public health through his easily-debunked claims, but it’s definitely a non-zero amount of damage. Same for Gomes et al.

      “Adopting insights from the Gomes article, the British statistician Nic Lewis suggests that Stockholm County in Sweden may indeed have already achieved herd immunity.”
      https://reason.com/2020/05/15/whats-the-herd-immunity-threshold-for-the-covid-19-coronavirus/

      • To be fair, I accidentally used “herd immunity” in the same context, and I know better. As you say, population immunity is correct, herd immunity is not only wrong, but dangerously wrong.

      • No problem. Technically, I’m using terminology in a particular way as well. For example, some people would use “population immunity” to mean the same thing as “herd immunity”, when using “herd immunity” in the R0 way I discussed before. Alternatively, others use “population immunity” as a matter of degree, where a population has more or less immunity (based on the proportion of those immune to infection), reaching “herd immunity” when they have a sufficient level of immunity. That latter definition of “population immunity” is the one I’m using. Examples of either definition below (note that the measles percentages in the 2nd link below from the WHO, are a homogeneity-based calculation from the insanely high R0 of measles virus, with a little added cushion for the vaccine failing in some people, etc.)

        ”Since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, most of the studies estimated the SARS-CoV-2 R0 to be in the range of 2 to 3. […] Assuming no population immunity and that all individuals are equally susceptible and equally infectious, the herd immunity threshold for SARS-CoV-2 would be expected to range between 50% and 67% in the absence of any interventions.
        […]
        An infection-based herd immunity approach (ie, letting the low-risk groups become infected while “sequestering” the susceptible groups) has been proposed to slow the spread of SARS-CoV-2. However, such a strategy is fraught with risks. For example, even with modest infection fatality ratios, a new pathogen will result in substantial mortality because most, if not all, of the population would not have immunity to the pathogen. Sequestering the high-risk populations is impractical because infections that initially transmit in low-mortality populations can spread to high-mortality populations. Moreover, so far, there is no example of a large-scale successful intentional infection-based herd immunity strategy.
        There are only rare instances of seemingly sustained herd immunity being achieved through infection. The most recent and well-documented example relates to Zika in Salvador, Brazil. Early in the COVID-19 pandemic, as other countries in Europe were locking down in late February and early March of 2020, Sweden made a decision against lockdown. Initially, some local authorities and journalists described this as the herd immunity strategy: Sweden would do its best to protect the most vulnerable, but otherwise aim to see sufficient numbers of citizens become infected with the goal of achieving true infection-based herd immunity. By late March 2020, Sweden abandoned this strategy in favor of active interventions; most universities and high schools were closed to students, travel restrictions were put in place, work from home was encouraged, and bans on groups of more than 50 individuals were enacted. Far from achieving herd immunity, the seroprevalence in Stockholm, Sweden, was reported to be less than 8% in April 2020,7 which is comparable to several other cities (ie, Geneva, Switzerland,8 and Barcelona, Spain9).”

        https://jamanetwork.com/journals/jama/fullarticle/2772167

        ‘Herd immunity’, also known as ‘population immunity’, is a concept used for vaccination, in which a population can be protected from a certain virus if a threshold of vaccination is reached.
        Herd immunity is achieved by protecting people from a virus, not by exposing them to it.
        […]
        The percentage of people who need to have antibodies in order to achieve herd immunity against a particular disease varies with each disease. For example, herd immunity against measles requires about 95% of a population to be vaccinated. The remaining 5% will be protected by the fact that measles will not spread among those who are vaccinated. For polio, the threshold is about 80%.
        […]
        Attempts to reach ‘herd immunity’ through exposing people to a virus are scientifically problematic and unethical. Letting COVID-19 spread through populations, of any age or health status will lead to unnecessary infections, suffering and death.”

        https://www.who.int/news-room/q-a-detail/herd-immunity-lockdowns-and-covid-19

        Either usage of “population immunity” is fine, as long as one is clear on what one means by one’s terms.

        What’s not OK is what Nic Lewis (and a number of other right-wing COVID-19 contrarians) did:
        Basically, these objectors want to claim that public health experts over-estimated the herd immunity threshold. Hence why Lewis named his original article ”Why herd immunity to COVID-19 is reached much earlier than thought“. So to fairly address those experts’ position, the objectors need to use the definition of “herd immunity” experts use in terms of R0. Otherwise, those objectors are attacking a straw man. Yet Lewis and the other objectors equivocated to a definition of “herd immunity” that was not about getting R below 1 under baseline conditions of R0, but instead about getting R below 1 under non-baseline conditions in which there were additional public health interventions and behavior changes (ex: reduced mobility / social interaction in Sweden, Sweden close down large gathers of over 50 people, Sweden closing secondary schools + universities, Sweden limiting visits to those in nursing homes, etc.).

        Lewis therefore either equivocated by switching from experts’ R0-based definition of herd immunity to his re-definition of it, oR Lewis didn’t know the definition experts used in epidemiology, immunology, etc. I’m leaning more to the latter option, since in my experience with Lewis, he doesn’t know much about my field of expertise (immunology).

  97. Some legit questions about the convenience sampling (there was some random sampling that showed lower attack rate) … but still:

    -snip-
    SARS-CoV-2 spread rapidly in the Brazilian Amazon and the attack rate there is an estimate of the final size of a largely unmitigated epidemic. We use a convenience sample of blood donors to show that by June, one month after the epidemic peak in Manaus, capital of Amazonas state, 44% of the population had detectable IgG antibodies. Correcting for cases without a detectable antibody response and antibody waning, we estimate a 66% attack rate in June, rising to 76% in October. This is higher than in São Paulo, in southeastern Brazil, where the estimated attack rate in October is 29%. These results confirm that, when poorly controlled, COVID-19 can infect a high fraction of the population causing high mortality.

    https://science.sciencemag.org/content/early/2020/12/07/science.abe9728

  98. We have potentially good news:

    “This means that for the last 10 days of data, death counts in Sweden must only be interpreted as incomplete measures of mortality.”

    I’ve been watching the 10 day lag deal. We are now three or four days past 10 days. The full definition says more than 10 days. But a reasonable person would think the further back in time we go, the less the chances of getting adds.

    We have been hoping for a leveling off. It may not be here. What we don’t seem to have is exponential growth which would be bad. It’s had plenty of time to ignite. That a country hanging by a thread would have gone up in flames by now. It hasn’t.

    Everything will Okay.

  99. Their ICU admissions rate has starte to level off. But it sure ain’t dropped. And it’s still going up.

    But…they’ve run out of room in their ICUs. They’re passing laws so they can shut down businesses. They’ve just shut down their middle schools. Why did they shut down their middle schools?

    You still don’t understand the lag. All this time and you still don’t get it. Must be a reason.

    They’re still adding deaths to over 17 days ago. Why are they still adding deaths to over 17 days ago? Yesterday they added deaths to their 7-day average for deaths on the 26th of November they added deaths today. It’s still going up. They are now listing 135 deaths between the 24th and 25th. Check back next Tuesday to see if it goes up again.

    Why do you never learn?

    Why do you not care that other people sacrifice? That other people’s family members die? Why don’t you care? I like to think it’s motivated reasoning. Maybe it’s Trump cultism. Maybe it’s just some twisted form of hatred of libz and demz and “the left. ” Because even that’s better than the alternative explanation.

    • Perhaps you realize what you’re doing. I read the deal. It said, blah, blah, blah, ten days. I am looking at that resolution. You are looking at the deaths from 17 days ago resolution. They don’t say 17 days ago. They do say 10 days ago. While I allow deaths prior to 10 days ago, we must be talking slivers when compared to the total volume under the curve.

      I am watching a podcast about fighter pilot David Fravor. Who saw something like a UFO. He said, 80/20 solution. My plots are the 80% solution. Yours are the 100% solution. I hope you know why that’s bad. It’s not time. It’s something else.

      Let me ask you something. Were people in Sweden dying from cancer 18 months ago? What did you say about that? Were people living in bleephole countries 18 months ago? Why do you not care that other people sacrifice?

      Lack of exponential growth is good. Exponential growth often groups with risk. Why don’t we get exponential growth. Typically it is not favored. Not favored by nature. There are exceptions. Ice taking over a lake in one night. But we aren’t dealing with something like that at this time. It’s not a developing thunderstorm. It’s raining. We aren’t stopping the rain.

      • > You are looking at the deaths from 17 days ago resolution
        No. I’m looking at a larger pattern.

        You keep trying to slice off as little as possible to justify your dismissal of the suffering and sacrifice of other people. Doing it once is understandable. Maybe twice or three times. Could be a misunderstanding. A learning curve. But when you do it over and over a lack of explanation becomes conspicuous.

        Forced to guess, I’d wonder if this isn’t overly pessimistic. But still…