The relative infectivity of the new UK variant of SARS-CoV-2

By Nic Lewis

Key points

  • A new variant, B.1.1.7, of the SARS-CoV-2 virus has recently spread rapidly in England
  • The public health agency’s best estimate of B.1.1.7’s weekly growth rate advantage is 1.51x
  • They mis-convert this in a reproduction number ratio of 1.47; converting appropriately gives a ratio of 1.25
  • Confident claims by the UK government scientific advisers that the higher growth of B.1.1.7 is due to increased transmissibility are misplaced; it could be partly of wholly due to other factors
  • 1.1.7 has not shown a greater growth rate advantage than two previous variants did, both of which are now thought to have no greater transmissibility than previously existing variants
  • There is little evidence that B.1.1.7 is more virulent, or likely to be resistant to existing vaccines

Introduction

The apparent rapid growth in England of a new variant of the SARS-CoV-2 virus that causes COVID-19 has led to dire warnings by those advising the UK government. Their advice suggested only that the new variant was more transmissible (more infective), not that it was more virulent (causes more serious illness). Nevertheless, it resulted in swift (many would say panicky) actions first by the UK government and then by governments of many other countries. The UK government imposed further restrictions on people’s freedom to mix and to move, while other countries banned travellers from the UK. Many millions of people in the UK had to cancel their plans for the Christmas holiday at very short notice, in addition to having their freedoms further curtailed thereafter. In this article I examine to what extent the advice that led to these damaging government actions was justified.

The new strain, B.1.1.7, and its spread in the UK

The UK government agency Public Health England (PHE) termed the new variant VUI-202012/01, and now VUC-202012/01, but I shall refer to it by the scientific name given to its lineage, B.1.1.7 (Rambaut et al.)[1], or just as “the new variant”. The lineage involves 8 amino acid changes (6 mutations and 2 deletions)[2] in the gene for the important spike protein, along with 9 amino acid changes[3] in genes for other proteins. The lineage has sometimes been referred to just by the name of the best known mutation it possesses, N501Y, but doing so is to be avoided as there are other variants that also have this mutation.

Rambaut et al. have this to say about the new lineage:

The B.1.1.7 lineage carries a larger than usual number of virus genetic changes. The accrual of 14 lineage-specific amino acid replacements prior to its detection is, to date, unprecedented in the global virus genomic data for the COVID-19 pandemic.

They also identify three of the mutations in particular (including N501Y) as being suspected of having potential biological effects.

B.1.1.7 was first detected in SARS-CoV-2 sequenced from a sample collected in south-east England on 20 September 2020, since when the cluster of cases has grown rapidly and spread to other locations. The UK sequences many more SARS-CoV-2 genomes than any other nation, and more than the rest of Europe combined, so the fact that B.1.17 was first detected in the UK does not necessarily imply that it originated there. The lineage has also been detected in several other countries and may well now be widespread.

Growth of the B.1.1.7 lineage in the UK can be tracked in sequencing data uploaded to GISAID. I used the COVID-CG processing facility[4] to select each day’s sequences with all eight B1.1.7 spike gene mutations.[5] As the daily data were noisy and few sequences were dated after 12 December 2020, I took 7-day moving averages, centred up to 9 December. Figure 1 shows the resulting proportion of all UK sequences represented by the B.1.1.7 lineage since its first emergence. It should be noted that the proportion of non-B.1.1.7 sequences represented by the areas in which B.1.1.7 first grew to prominence may have increased over time, resulting in the growth shown overstating how fast it grew in individual areas or in the UK as a whole.

 

Figure 1. The proportion of all SARS-CoV-2 genomes sequenced in the UK made up by the B.1.1.7 lineage

The higher growth rate of B.1.1.7

A PHE report published on 21 December 2020[6] presents epidemiological evidence about the growth rate of B.1.1.7 relative to non-B.1.1.7 lineages. By using a proxy marker for B.1.1.7[7] they were able to utilise data from a significant proportion of the UK ‘pillar 2’ testing programme. Doing so provided a much larger dataset than that of sequenced SARS-CoV-2 genomes, and enabled stratification of weekly data for each of 42 NHS “STP” areas. Figure 2 reproduces Figure 1 of the PHE document, which shows the multiplicative advantage in weekly growth rates of B.1.1.7 cases (the ratio of B.1.1.7 to non-B.1.1.7 week t+1 cases divided by week t cases). The x-axis is for the B.1.1.7 proxy, S gene test negative. The week stated is the base week, so the yellow points reflect ratios of week 49 (week ending 5 December) cases to week 48 cases.

Figure 2. Empirical data analysis of the multiplicative advantage in weekly growth rates. Each point represents the ratio of weekly growth rates between B.1.17 [VOC] and non-B.1.1.7 for an NHS England STP area and week, based on the pillar 2 data shown in Figure S1 of the PHE report. Colours and shapes differentiate calendar weeks. Numbers above 1 show a multiplicative advantage. The blue line represents the mean value for a particular frequency, and the grey lines the 95% envelope. Scatter at low frequencies largely reflects statistical noise due to low counts.

When the new variant represents a small proportion of total cases (under ~ 25%, say), the proxy used is less satisfactory, and there is also a lot of scatter. Nevertheless, the variant’s proxy-based mean multiplicative advantage (ratio) in weekly growth is remarkably independent of its relative prevalence. That supports PHE’s methodology, although the week 48 data suggests that the multiplicative advantage might decline once the variant makes up more than ~25% of the total cases. PHE compute from this data a mean multiplicative advantage in weekly growth of 1.51 for B.1.1.7. By assuming a fixed generation interval of 6.5 days, they convert this into a reproduction number (Rt) multiplicative advantage of 1.47 for B.1.1.7 relative to other variants,.

PHE also estimated the effect of B.1.1.7 on Rt using genomic (sequencing) data for the same areas and weeks. They estimated an additive effect on Rt of 0.57, or 0.74 when the effect was allowed to vary between areas. PHE also estimated the effect on Rt using the PCR test S gene proxy data, adjusted for specificity (which is poor when the S gene negative proportion is low). Their estimates of the additive effect on Rt using that data were 0.52, or 0.60 when the effect was allowed to vary between areas. Using a Bayesian regression model their estimate of the effect was 0.56. However, since any biological difference in infectivity would be expected to cause a multiplicative effect on Rt, and Rt was varying during the analysis period, an estimated additive effect on Rt is less useful and also liable to be less accurate than a multiplicative estimate. In addition all these estimates involve more complicated statistical models, further assumptions and estimates of other variables. I therefore prefer their estimated multiplicative advantage of 1.51 (for weekly growth, prior to conversion to Rt scale), which is directly derived from underlying data. This is equivalent to a logarithmic daily growth rate advantage of 0.059.

Other evidence regarding the faster growth of B.1.1.7

A meeting of the NERVTAG[8] committee – which advises the government on the threat posed by new and emerging respiratory viruses – on the new variant took place on the 18 December 2020. The minutes[9] refer to an estimate from genomic data of a growth rate 71% higher than other variants; none of the documents that was considered by the committee contained such an estimate. It appears from the minutes of a subsequent meeting on 21 December 2020[10] that this was one of several undocumented estimates from NERVTAG member Professor Neil Ferguson of Imperial College. An alternative regression estimate that he apparently presented indicated that lineage B.1.1.7 had a Rt 0.39 higher than non-variant lineages from early November to early December. This is presumably an additive effect estimate, and is noticeably lower than PHE’s estimates using much the same method. Two other estimates stated in the minutes to be from Professor Ferguson both appear to actually be slightly misstated versions of the PHE estimate of a multiplicative Rt advantage of 1.47 for B.1.1.7.

The minutes of a further NERVTAG meeting the 21 December also mention a London School of Hygiene and Tropical Medicine estimate that B.1.1.7 was 56% more transmissible (a multiplicative advantage of 1.56 in Rt value). This estimate is documented in a preprint (Davies et al.[11]). The authors use a Subjective Bayesian method to fit a highly complex model with many probabilistic parameters, some fixed and others estimated. This is a far from robust, and quite possibly inherently biased, method of estimating the relative transmission rate. Moreover, they appear to use less informative data, broken down geographically only by the 7 NHS regions, not (as PHE used) by the 42 NHS STP areas. The use of less informative data implies that, even if they had employed a robust method, their estimates would be expected to be inherently less reliable than the PHE estimate.  The uncertainty ranges of their estimates – which include a 99%+ confidence interval of 1.49x to 1.57x for the South East[12] region – appear to be quite unrealistically narrow, given the substantial uncertainties that exist. That casts further doubt on the realism of their estimates.

Finally, the NERVTAG 21 December meeting also considered a University of Edinburgh (Andrew Rambaut) phylogenetic estimate based on genetic sequences from Kent and London, that Rt was 1.57 or 1.72 depending on the time window used. Since no comparative Rt estimate for non-B.1.1.7 variants is mentioned in the meeting minutes, it is not possible to infer from this an estimate of the relative transmission rate of the new variant.

I conclude that the other evidence considered by NERVTAG is less robust and less useful than the PHE estimate of a multiplicative advantage in weekly growth of 1.51.

Why the faster growth of B.1.1.7 need not be due to increased transmissibility

While the evidence that the B.1.1.7 lineage has grown faster than other lineages in England over the  two months or so to early/mid-December seems robust, one cannot infer biological properties of a virus from limited epidemiological data only. The apparent rapid spread of this new variant might be due to founder effects and super-spreader events rather than, or in addition to, increased transmissibility (higher infectivity).

It is instructive in this regard to consider two other lineages/variants that also had a period of exceptionally fast growth and, in one case, came to be totally dominant in most countries.

The G clade: spike gene mutation D614G

The D614G mutation arose early in the epidemic, emerging in Europe in February, and the G614 variant undoubtedly spread faster in most locations than D614. In very many countries, areas and cities it went from representing a minority of infections to being the dominant variant within a period of month or so. Since July 2020 it has accounted for approaching 100% of new infections in most countries and in all continents.

In the light of D614G becoming and remaining so dominant, it is unsurprising that a paper in August (Korber et al.[13]) argued that the D614G mutation increases transmissibility, citing several pieces of evidence:

  • the consistency of increase [in frequency of G614] across geographic regions.
  • the D614 form did not persist in many locations where the G614 form was introduced into the ongoing well-established D614 epidemics, as would be expected if the two forms were equally likely to propagate.
  • the increase in G614 frequency often continued well after national stay-at-home orders [lockdowns] were in place, when serial reseeding from travellers was likely to be reduced significantly.

In addition to that epidemiological evidence, the authors also noted that increased transmissibility of G614 was consistent with other studies that suggested associations with increased infectivity in vitro[14] [15], and with their own finding of an association with higher viral loads in vivo. Moreover, another paper (Li, Q et al[16]) reported higher antigenicity for G614.

Most of Korber’s arguments are also fairly applicable to evidence suggesting that B.1.1.7 may be more transmissible. However, a more recent paper in Nature (van Dorp et al.[17]) found “no evidence for significantly more transmissible lineages of SARS-CoV-2 due to recurrent mutations”, including D614G (B.1.1.7 had not been identified by the end of the study period). This shows that, even after a new strain has become dominant, conclusions about its relative transmissibility drawn from epidemiological and indirect biological evidence may turn out to be wrong.

The 20A.EU1variant: spike mutation A222V

The 20A.EU1 variant, which involves spike gene mutation A222V, emerged in Spain in early summer 2020. It rapidly spread to other European countries, where it typically grew faster than non-20A.EU1 variants. Figure 3 plots the logarithmic daily growth rate of sequences with the A222V mutation in the UK, relative to those without it, over the two months to mid-September. Over that period the ratio of A222V to non-A222V new sequences grew from under 0.02 to 0.67. The mean logarithmic daily growth rate was 0.061 – a weekly multiplicative advantage of 1.53 – with essentially no trend. That multiplicative advantage is effectively identical to the 1.51 estimate by PHE for B.1.1.7 using data from mid-October to mid-December.

Figure 3. The logarithmic daily growth rate of the 7-day moving average of new sequences with the A222V mutation in the UK, relative to those without it, over the two months to 12 September 2020.

However, in the autumn the relative frequency of new A222V sequences stopped increasing in a number of countries, without – as D614G did – achieving total and continuous dominance (Figure 4). In the UK the A20.EU1 variant reached some 70% of all new sequences by the end of October, but it has since declined in relative frequency, as it has also done in Belgium, Germany and Switzerland.

Figure 4. The proportion during 2020 of weekly new SARS-CoV-2 sequences in ten European countries that have the A222V mutation (implying they are the A20.EU1 variant)

Notwithstanding the rapid growth of the 20A.EU1 variant in many European countries during the summer and/or autumn, a November 2020 preprint paper about 20A.EU1 concluded: “We find no evidence of increased transmissibility of this variant, but instead demonstrate how rising incidence in Spain, resumption of travel across Europe, and lack of effective screening and containment may explain the variant’s success”.[18]

Overestimation of effect on Rt of possible increased transmissibility

Supposing that the higher growth rate to date of the B.1.1.7 lineage were all due to higher transmissibility, what effect would this have on the current reproduction number, Rt? That will depend on what Rt is and on the mean generation interval and its probability distribution. The longer the generation interval, the higher Rt required to produce a given growth rate. In the 21 December PHE publication, their estimate of the multiplicative advantage in weekly growth rate (of 1.51) is converted to a multiplicative advantage in Rt of 1.47 by assuming a fixed generation interval of 6.5 days: 1.47 = 1.51^(6.5/7).

However, PHE’s conversion formula is not justified, for two reasons:

  • the generation interval is not fixed; and
  • recent estimates of the mean generation interval are well below 6.5 days.

Most estimates of the generation interval (the period from one person being infected to them infecting another person) are in fact estimates of the serial interval (the period from the symptom onset in one person to symptom onset in a person they infect), since the time of infection is not observable. The generation interval can be validly estimated by combining probabilistic estimates of the serial interval and the incubation period (from infection to symptom onset). However, simply treating a probabilistic serial interval estimate as representing the generation interval distribution, as is typically done, is unsatisfactory.

PHE give no source for their assumption of a 6.5 days generation interval, but they could be following the Imperial College team, who used (in Flaxman et al.[19]) a generation interval with a 6.5 days mean, stating it was estimated by Bi et al.[20]. In fact, Bi et al. estimated the serial interval, not the generation interval, and fitted a gamma probability distribution with a mean of 6.3 days. However, their data included cases where the infecting individual did not isolate from others until long after symptom onset. Bi et al. found that if the infected individual was isolated less than three days after symptom onset, which would normally be the case in the UK now, the average serial interval was only 3.6 days.

Knight and Mishra (2020)[21] show that, to avoid overestimating the serial interval, it needs to be fitted to a probability distribution that, unlike the gamma distribution used by Bi et al., permits negative values (which are observed in a non-negligible proportion of cases). They consider a number of estimates examined in a review article of the incubation period and the serial interval, selecting the only serial interval estimate based on a negative-permitting probability distribution that had a large sample size (nearly ten times as large as that in Bi et al.), and the incubation period estimate that was based on the largest sample. Their resulting generation interval estimate has a mean of 3.99 days and a standard deviation of 2.96 days.[22]

Davies et al. say that their complex Bayesian model, which estimated a multiplicative advantage of 1.56 in Rt value using a fairly long generation interval, fitted less well when they used a shorter interval. However, it seems probable that the main reason they obtain a poor fit to the relative growth in the new variant during lockdown with a shorter generation interval is that their model greatly overestimates the effect of the November lockdown. [23]

Using the Knight and Mishra estimated distribution for the generation interval, and the correct conversion formula,[24] the PHE estimate of the B.1.1.7 lineage’s multiplicative advantage in weekly growth rate of 1.51 corresponds to a multiplicative advantage in Rt of 1.25.[25] That is only about half the multiplicative advantage of 1.47 estimated by PHE.[26] It implies that less extensive and severe measures would be required to prevent exponential growth of infections given the emergence of B.1.1.7 than is implied by the PHE estimate of a 1.47 multiplicative advantage in Rt, even if the observed multiplicative advantage in weekly growth rate of B.1.1.7 to mid-December is entirely caused by it being more transmissible.

The new South African variant

A new SARS-CoV-2 lineage that also involves a N501Y spike gene mutation, and a number of other mutations (differing from those in B.1.1.7),  has recently emerged in South Africa, as described by Tegally et al.[27], who term it 501Y.V2. They say that genomic data, showing the rapid displacement of other lineages, suggest that this lineage may be associated with increased transmissibility. However, the limited evidence available so far is insufficient to justify the alarmist comments from the UK government health minister, that “This new variant is highly concerning because it is yet more transmissible and it appears to have mutated further than the new variant discovered in the UK”.[28] As a professor of molecular virology at the University of Nottingham stated, the mutation involved has been seen before, we have no idea whether it impacts on virus transmissibility, and we should avoid panicking at this point.[29]

Conclusions

The G clade and 20A.EU1 examples illustrate that apparently strong epidemiological evidence of a higher growth rate of a new variant over considerable period, even where it leads to apparently permanent dominance, and notwithstanding it being accompanied by evidence suggesting that the variant is associated with higher viral loads, does not enable a valid conclusion that the variant has higher transmissibility than existing variants. Such evidence may be suggestive of higher transmissibility, but it does not reliably demonstrate it.

Despite this, the NERVTAG committee concluded with moderate confidence on 18 December that the new variant “demonstrates a substantial increase in transmissibility compared to other variants” and at their 21 December meeting went further and expressed high confidence that “B.1.1.7 can spread faster than other SARS-CoV-2 virus variants currently circulating in the UK”. While admitting that the underlying cause of faster spread was unclear, the causative factors that they suggested related exclusively to higher transmissibility. It is not surprising, given that NERVTAG’s confident conclusions are not justified by the facts,  that a number of experts in the UK and other countries have disputed them[30] or expressed contrary views,[31] [32] [33] Unsurprisingly, the mainstream media are reporting, incorrectly, that B.1.1.7 has been proven to possess substantially increased transmissibility.

I have argued that the estimate by PHE of a multiplicative weekly growth advantage of 1.51 for B.1.1.7 is, for several reasons, more robust and accurate than the other available estimates. I have shown that, even if the higher growth to date of B.1.1.7 were due entirely to increased transmissibility, it would correspond to a multiplicative advantage in Rt of only 1.25, half as high an advantage as calculated by PHE using an inappropriate conversion formula.

There is no evidence to date that B.1.1.7 is any more any virulent than existing strains, nor that it will be resistant to the vaccines that have been developed. Expert opinion appears to be that neither of these are likely to be the case.[34]

These findings imply that B.1.1.7 does not currently appear to represent a serious increase in the menace posed by SARS-CoV-2, even in the worst case that its higher observed growth rate is entirely due to increased transmissibility. In the best case, its higher growth rate will turn out not to spring to any extent from increased transmissibility, as now appears to be the case with the G clade and 20A.EU1 variant.

Accordingly, it is difficult to see that imposing drastic measures to slow transmission, further reducing economic activity, social activity and peoples freedom, are justified by the current evidence regarding  the emerging B.1.1.7 lineage.

However, as further evidence becomes available it could strengthen, or weaken, the case that the emergence of B.1.1.7 represents a serious development. It is important that the UK authorities start to release, on a daily basis and at local authority area or finer level, all available data on cases of  the new strain, as indicated by the ‘S gene negative’ proxy and any other method. At present they are keeping this information non-public, which makes it impossible for independent researchers properly to assess on a timely basis, and if necessary challenge, what may be mistaken conclusions. Moreover, it is highly desirable that no SARS-CoV-2 or COVID-19 related report or study should hereafter be considered by the government or its advisers unless it is accompanied by a link at which all the data used is available.

Nicholas Lewis                                                                                   29 December 2020


[1]  Rambaut, A et al:  Preliminary genomic characterisation of an emergent SARS-CoV-2 lineage in the UK defined by a novel set of spike mutations. COVID-19 Genomics Consortium UK, ARTIC network 19 December 2020.  https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563

[2]  N501Y, A570D, P681H, T716I, S982A and D1118H mutations plus HV69-70 and Y144 deletions

[3]  T1001I, A1708D and I2230T mutations plus SGF3675-3677 deletion in the ORF1ab gene; R52I and Y73C mutations plus Q27stop codon in the Orf8 gene; D3L and S235F in the N gene. There are also 6 synonymous (non-amino acid changing) mutations: 5 in ORF1ab (C913T, C5986T, C14676T, C15279T, C16176T), and 1 in the M gene (T26801C).

[4]  https://www.covidcg.org/?tab=location# . Data downloaded 26 December 2020.

[5]  Only the total number of each day’s sequences with each mutation are available via COVID-CG, but the number of each of the eight spike mutations appearing each day (r >0.999, except 0.991for the HV69-70 deletion, which sometimes occurs in other strains), implying that they have an extremely high co-occurrence. I took the minimum number each day for the eight spike mutations as the count for B.1.1.7 sequences. Incorporating non-spike mutation data appears unnecessary; the match of all B.1.1.7 spike mutations with all ORF1ab B.1.1.7 mutations is almost perfect apart from  A1708D, which seems absent in about 1% of cases where all 11 other spike and ORF1ab mutations are present.

[6]  Public Health England: Investigation of novel SARS-COV-2 variant – Variant of Concern 202012/01. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/947048/Technical_Briefing_VOC_SH_NJL2_SH2.pdf

[7]  S gene negative, N and ORF1ab positive TaqPath PCR test result.

[8]  NERVTAG: New and Emerging Respiratory Virus Threats Advisory Group

[9]  NERVTAG COVID-19 VUI communication 18122020_final.pdf, available at https://app.box.com/s/3lkcbxepqixkg4mv640dpvvg978ixjtf/folder/111416414559

[10] NERVTAG COVID-19 VOC communication 21122020 final.pdf, available at https://app.box.com/s/3lkcbxepqixkg4mv640dpvvg978ixjtf/folder/111416414559

[11] Davies, NG et al: Estimated transmissibility and severity of novel SARS-CoV-2 Variant of Concern 202012/01 in England. Centre for Mathematical Modelling of Infectious Diseases,  London School of Hygiene and Tropical Medicine, updated 23 December 2020. https://cmmid.github.io/topics/covid19/reports/uk-novel-variant/2020_12_23_Transmissibility_and_severity_of_VOC_202012_01_in_England.pdf

[12] Figure1A of Davies et al, rightmost panel.

[13] Korber, B. et al. Tracking changes in SARS-CoV-2 spike: evidence that D614G increases infectivity of the COVID-19 virus. Cell 182, 812.e19–827.e19 (2020). https://doi.org/10.1016/j.cell.2020.06.043, 20 August 2020

[14] Zhang, L. et al. The D614G mutation in the SARS-CoV-2 spike protein educes S1 shedding and increases infectivity. Preprint at https://doi.org/10.1101/2020.06.12.148726, 12 June 2020

[15] Yurkovetskiy, L. et al. Structural and functional analysis of the D614G SARSCoV-2 spike protein variant. Cell 183, 739.e8–751.e8 https://doi.org/10.1016/j.cell.2020.09.032, October 2020

[16] Li, Q. et al. The impact of mutations in SARS-CoV-2 spike on viral infectivity and antigenicity. Cell 182, 1284.e9–1294.e https://doi.org/10.1016/j.cell.2020.07.012, September 2020

[17] van Dorp, L et al., No evidence for increased transmissibility from recurrent mutations in SARS-CoV-2. Nature, November 2020. https://doi.org/10.1038/s41467-020-19818-2

[18]Hodcroft, BH et al: Emergence and spread of a SARS-CoV-2 variant through Europe in the summer of 2020.  medRxiv 27 November 2020 https://doi.org/10.1101/2020.10.25.20219063

[19] Flaxman, S., Mishra, S., Gandy, A. et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Nature 584, 257–261 (2020). https://doi.org/10.1038/s41586-020-2405-7

[20] Bi, Q. et al. Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts. medRxiv (2020) https://doi.org/10.1101/2020.03.03.20028423

[21] Knight, J. and Mishra, S.: Estimating effective reproduction number using generation time versus serial interval, with application to COVID-19 in the Greater Toronto Area, Canada. Infectious Disease Modelling 5 (2020) 889e896, November 2020.  https://doi.org/10.1016/j.idm.2020.10.009

[22] Knight and Mishra fit their generation interval estimate using a gamma distribution. Unlike the serial interval, the generation interval cannot be negative so a gamma distribution is suitable here.

[23] They say that the poor fitting with a shorter generation interval was because it predicted that the new strain should have decreased in relative frequency during November’s lockdown. As they write: “When Rt < 1 for both variants, a shorter generation time is a selective disadvantage, because infections with this variant decline faster compared to a variant with the same Rt but transmitting on a longer timescale.” However, that is only true if Rt was below 1 during lockdown, whereas their Fig. 1E shows that, in reality, Rt remained at or marginally above 1 during lockdown. That is consistent with the mobility data in Davies et al. Fig.1C, which show little difference between immediately prior to the start and the end of lockdown. An overall Rt of 1 implies that the infections with the more transmissible variant will increase in relative frequency, as occurred, not decrease. Also, the complexity of their model means that the poor fitting could to be partially or wholly due to other causes, such as a long generation interval compensating for another parameter being misestimated, or to the peculiar way in which they represented a shortened generation interval.

[24] Wallinga, J., & Lipsitch, M. (2007). How generation intervals shape the relationship between growth rates and reproductive numbers. Proceedings of the Royal Society B: Biological Sciences, 274(1609), 599-604. https://doi.org/10.1098/rspb.2006.3754 Using their equation 2.9 in conjunction with the gamma distribution moment generating function.

[25] The estimate of the multiplicative advantage assumes that Rt for the other strains is 1.0; the inferred multiplicative advantage is a slowly decreasing function of Rt for the other strains.

[26] The same is approximately true throughout PHE’s 95% confidence interval of for the Rt ratio of 1.34–1.59, which when converted in the same way corresponds to an Rt ratio range of 1.19–1.30.

[27] Tegally, Houriiyah, et al. “Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa.” medRxiv 22 December 2020. https://doi.org/10.1101/2020.12.21.20248640

[28] As quoted in the Guardian, 23 December 2020. https://www.theguardian.com/world/2020/dec/23/south-african-covid-19-variant-has-reached-the-uk-says-matt-hancock

[29] Professor John Ball, as quoted at https://www.sciencemediacentre.org/expert-reaction-to-south-african-variant-of-sars-cov-2-as-mentioned-by-matt-hancock-at-the-downing-street-press-briefing/

[30] Vincent Racaniello, Professor of Immunology, Columbia University. Extensive detailed comments, including that “none of the isolates so far have proven implications for human transmission or pathogenesis, including the latest variant isolated from the UK.” and, concerning the NERVTAG 21 December meeting: “You can’t use epidemiological data to prove a biological effect of a amino acid change in a virus; you have to do experiments to do that. And that’s what they’re doing here. They say, there is an increase in the transmissibility. It must be because of the variant. Well, obviously that’s a flawed argument. That’s not how we do science.” https://www.virology.ws/2020/12/24/sars-cov-2-uk-variant-does-it-matter/ ; transcript at https://dryburgh.com/vincent-racaniello-coronavirus-variant-voc-202012-01/

[31] Dr Julian Tang, Honorary Associate Professor/Clinical Virologist, University of Leicester, said:
“The spread of this new virus variant could be due to many factors.  As we saw with the earlier D614G variant – just higher viral loads in clinical diagnostic swabs or in cell culture may not necessarily translate to a more transmissible virus at the population level.
“A higher genomic growth rate in the samples sequenced, may not necessarily mean higher transmissibility, e.g. if there was a rave of several thousand people where this variant was introduced and infected many people mostly in that rave, this may seem very high compared to a lower background of non-variant virus, e.g. in an otherwise prevailing national lockdown.” https://www.sciencemediacentre.org/expert-reaction-to-brief-summary-of-nervtag-opinion-from-the-nervtag-meeting-on-sars-cov-2-variant-under-investigation-vui-202012-01/

[32] Professor Vineet Menachery, University of Texas Medical Branch, said: “So this isn’t the first time we’ve seen variants emerge quickly or begin to dominate the population of viruses that we’re seeing. And so I’m not particularly worried at this moment. There is evidence that it is maybe slightly more transmissible, but we’re not at this point knowing enough about it to really be scared in the sense that it’s a different order of magnitude, that it’s going to be a major threat moving forward.” https://health.wusf.usf.edu/npr-health/2020-12-21/new-coronavirus-variant-found-in-u-k-what-does-it-mean-for-the-world

[33] Dr Nusrat Homaira, Respiratory Epidemiologist, UNSW Sydney. “There is modest evidence suggesting that this new variant of Sars-CoV-2 is more transmissible, and is speculated to be the reason for the recent increase in the number of Covid-19 cases in London, South East, and East of England regions.” https://www.dhakatribune.com/opinion/op-ed/2020/12/24/the-new-variant-of-the-sars-cov-2-what-it-all-means

[34] Dr Julian Tang, Honorary Associate Professor/Clinical Virologist, University of Leicester, said: “We are not seeing any increased virulence (clinical severity) or any gross changes in the S (spike protein) that will reduce vaccine effectiveness – so far.” https://www.sciencemediacentre.org/expert-reaction-to-brief-summary-of-nervtag-opinion-from-the-nervtag-meeting-on-sars-cov-2-variant-under-investigation-vui-202012-01/

Originally posted here, where a pdf copy is also available

279 responses to “The relative infectivity of the new UK variant of SARS-CoV-2

  1. The genome change and continued vaccine efficacy gives me a question for someone more knowledgeable: What prevents the mRNA vaccine from triggering immune response against valuable hormones; since some hormones also use “spike” (Glyco)proteins?

    • That’s an interesting question that I really don’t know the answer to. However, I think it is why mRNA vaccines have take decades to come to market. I think there is some magic in the delivery mechanisms and some of it may be proprietary.

      Here is quote from a Moderna SEC filing:

      “We pursue mRNA science both to minimize undesirable activation of the immune system by mRNA and to maximize the mRNA potency of mRNA once inside target cells. We pursue delivery science to protect mRNA from extracellular enzymes that would degrade it, to avoid counterproductive interactions of our delivery vehicles with the immune system, deliver mRNA to desired tissues, and facilitate mRNA transport across cell membranes to the translational machinery within cells”.

      https://www.sec.gov/Archives/edgar/data/1682852/000168285220000006/moderna10-k12312019.htm

    • “What prevents the mRNA vaccine from triggering immune response against valuable hormones … ”

      The vaccine does not trigger an immune response against any hormone. The vaccine prepares the patient’s immune system to make an immune response to a protein (specifically a “spike” protein) that exists only on the surface of a Covid-19 virus when it shows up in the body. That immune response kills the Covid-19 virus. The immune response does not harm any other cells.

      https://www.cdc.gov/vaccines/covid-19/hcp/mrna-vaccine-basics.html

    • The mRNA vaccine is surrounded with a layer of lipid that fuses with human cell membranes and allows the mRNA enter human cells. Lipids have been used in cell culture experiments for more than 30 years to allow cells to take up foreign DNA or RNA (“transfection). The mRNA is accepted by ribosomes, the machinery inside cells that “translates” mRNA into proteins. Some existing gene therapy protocols and some DNA vaccines use lipids to help DNA enter cells, but most incorporate the therapeutic DNA into a relatively harmless virus that already knows how to enter human cells more efficiently.

      The mRNA causes some human cells it enters to produce a subunit of the SARS-CoV-2 spike protein. Your immune system creates antibodies that bind with high affinity and selectivity to the spike protein subunit – and if we are lucky also to the spike protein in whatever strain of SARS-CoV-2 we may encounter for the next few years. Since we understand exactly which amino acid residues on the spike protein are essential for binding to the ACE2 receptor and essential for infecting human cells, and since we know the antibodies we create bind those same amino acids, there is good reason to expect that mutant viral strains that aren’t recognized by the antibodies also won’t be able to infect humans cells very efficiently. Antibodies are highly selective in what they bind to: they won’t bind to your proteins or hormones and probably not to the spike protein from the coronaviruses that cause the common cold or SARS-CoV-1. Antibodies are a highly selective means of distinguishing between foreign and host proteins. Autoimmune diseases are the result of antibodies recognizing proteins made by you, so evolutions has engineered antibodies to be highly selective to avoid this problem. None of the 20,000 vaccinated in clinical trials developed an auto-immune disorder. A few people with severe allergies have experienced immediate reaction to vaccination similar to the immediate allergic reaction to a bee sting.

      Since mRNAs are degraded within a few days, no trace of the mRNA remains in your body. Likewise, the protein made from the mRNA is also degraded after being recognized as foreign by your immune system. Other vaccines consist of weakened viruses (which replicate in your body), dead viruses (which often don’t induce a strong immune response) or DNA encoding for viral proteins (which can be incorporated into your DNA).

  2. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 – Climate- Science.press

  3. archibaldtuttle

    The money quote is the conclusion of the conclusion:

    “It is important that the UK authorities start to release, on a daily basis and at local authority area or finer level, all available data on cases of the new strain . . . At present they are keeping this information non-public,”

    Information is power. This seems a reasoned critique in the Hitchhikers Guide to the Galaxy meme of “Don’t Panic”, while not discounting plausible indications of increased transmissibility. As usual, the equally plausible concern continues to be for availability of raw data such that the science can be critiqued and/or replicated, an apparently bothersome requirement whether in climate or covid is involved, i.e. anything that is a big public policy driver.

  4. Nic, thanks, your research is superb but I’m wondering if you could provide an example demonstrating how a variant could dominate without being more contagious. I would like to visualize how founders effect would work in the midst of epidemic to amplify one variant to become dominant. My current thinking is that equally contagious mutations would simply lead to variety in the virus population. And how did the February European strain become dominate without being more contagious than the original?

    • Besides the importance of policy makers understanding of this it also goes to the virus’s natural origin theories. If very slight advantages have such profound effects on propagation it makes it implausible that a virus would could skip to another animal, adapt to that host, and then return to its first host species to outcompete its original strain. But this route is what is being postulated by this recent paper to explain why CoV2 is 96% genetically similar to a bat virus collected in Yunan province of China in 2013, and only 91% similar (overall) to pangolin-CoV, which has a similar spike to CoV2.

      From the paper: “Our analyses provide further support that SARS-CoV-2 originated from bats, considering that bat isolates may be the major parent contributing the largest fraction of sequences [explaining the 96% similarity to Cov2] ….Bat coronaviruses may have more chances to take part in recombination than coronaviruses from other hosts and thus play the most important role in the origin and recombination of human coronaviruses among all known coronavirus hosts [explaining their assertion of the uptake of the pangolin spike protein].”
      https://www.nature.com/articles/s41598-020-78703-6

      • Ron wrote: “Evolutionary forces thus drive the virus to be less and less incapacitating but more and more infectious to the host species. This is why most viruses can’t jump and propagate in the non-host species, but if they do they are usually more harmful. That NIH scientists felt that making lab chimera bat-human viruses was too dangerous to do in the USA but fine to fund Chinese research was nuts.

        Since SARS-CoV-2 is not very incapacitating and highly transmissible, I don’t think much evolutionary advantage will drive evolution of a less incapacitating strain. The fact that something like 50% of people are asymptomatic is a clear sign of this.

        Questions were raised about the risks and benefits of laboratory experiments (“gain of function” experiments) that attempt to simulate in the laboratory the evolutionary process of adapting a wild viral strain (say from bats) to efficiently replicate in a human cell line or a lab mammal. The goal was to safely create and study the kind of threats we anticipated encountering in the future – in the safety of a specially-designed laboratory. Such experiments were being done in one or two dozen laboratories around the world, including Wuhan’s. when serious questions arose, the NIH stopped such experiments (including those in Wuhan) while the risks were assessed. The assessed risk was cumulative: several dozens labs carrying out such experiments over several decades given the escape rate and accident rate experienced by such labs in the past. Based on that analysis, the experiments were allowed to resume. On that basis, the chance of an accidental escape occurred in Wuhan in October or November of 2019 must have been minuscule. Since every other viral pandemic in history has begun with natural adaptation of a virus to humans (or more likely first to [domesticated] animals that live near humans), we don’t need to postulate that something novel – human experiments – must have created the SARS-CoV-2.

        The mystery about SARS-CoV-2 is why COVID was first identified in Wuhan, which is far from the logical place of origin – bat-infested Southern China. This was the location that another deadly coronavirus from bats emerged less than two decades earlier. That virus was too incapacitating and deadly to escape Southern China without being detected and identified. My hypothesis is that we think of Wuhan as the source of COVID, when it was merely the location of the first super-spreader event(s) in a major city (with the medical sophistication to the identify the disease). IMO, COVID likely originated in rural Southern China and was carried undetected to Wuhan in a person or a short chain of people or via infamous wild animals the Chinese like to consume. Wuhan is a city bigger NYC with the largest wild animal market in Central China a perfectly logical place for COVID to emerge from either source. Yes, we know there were COVID cases in early December that were not directly linked to that market, but the ancestor to the initial three strains sequenced existed in November or possibly late October. And that ancestor virus could have existed in the live animal market or a person who worked there. (The Chinese government destroyed all samples, so we will never know if their neglect of the wild animal trade allowed a pandemic virus to reach a major city unidentified.)

        It is even easier to stop thinking of Wuhan are the birthplace of COVID (rather than the site of the first super-spreader events) when you recognize that in December 2019, the virus traveled unnoticed to France, was transmitted from one patient to another there, and disappeared. Given that the virus got to France unnoticed in December, it certainly could have gotten from South China to Wuhan unnoticed in November. You may also remember that there were COVID cases in California and Washington in January that went unidentified for several months even though US doctors were alert and knew what to look for at that time.

        I don’t want to say it rudely, but the idea that SARS-CoV-2 originated in a Wuhan laboratory resembles a conspiracy theory – driven by bias against China, the Communist Party’s lack of transparency, and a desire to blame someone else for our failures,

      • Frank, I agree that Wuhan was not necessarily the origin of the virus. However, the Chinese could realize this, which makes it curious to not allow the international community to trace the origin or find it themselves. Instead, they tried (unsuccessfully) to place the origin as the wet market. We know now that the cluster at the wet market was “just a coincidence” in looking similar to the 2002 SARS outbreak.

        You pointed out that China destroyed the RNA samples that would have aided in tracing the origin of a deadly threat in their own backyard that supposedly is still lurking. There is only one logical reason for doing this I can think of. After all, you pointed out that the storage of the virus has little risk compared with the benefit. Your information about the NIH is a different story from what I read and would appreciate the link. I believe the NIH determined in 2013 that the benefit of making chimeras to study was NOT worth the risk, considering the lab accidents that had been documented at the time. The only reason that Baric’s WIV chimera research was allowed to continue was that he specifically lobbied to have his research grandfathered from the ban. My personal hunch is that he wanted to prove the effectiveness of Remdesivir, which U of NC was partnered on. His paper acknowledged the failure of tried antivirals on the chimera and also that the chimera was even more viable than expected and thus more risky than feared.

        You are not disputing that the Chinese military was doing bat virus research in recent years and that they took control of the WIV when Covid hit. The Chinese military’s theory on origin, BTW, includes the US military.

        All this said I realize that half the people will see these facts as only evidence of conspiracy theory. Their reading of the admittedly closed and paranoid Chinese authorities is that they cover up everything reflexively, and since this behavior is normal it’s not suspicious.

      • Here is the article that Tucker Carlson pointed out last night on the likely lab origin of CoV2. This very well-researched New YorK Magazine article published yesterday shows the history of the gain of function research and its strategy: to create human pandemic viruses before nature can in order to keep them trapped in a lab where they could be studied. The gamble was that we could create safe and effective anti-virals and vaccines before we would need them to address a natural pandemic.

        Depending on whether you were a virus-engineering expert or not seems to dictate one’s opinion on whether this strategy was sound and whether the Covid-19 pandemic proves more gain of function research, (making nasty human transmitted viruses in the lab), is called for or not.

        https://nymag.com/intelligencer/article/coronavirus-lab-escape-theory.html?utm_source=tw&utm_medium=s1&utm_campaign=nym

      • Ron Graf asked about this article in The New Yorker on the origin of SARS-CoV-2.

        https://nymag.com/intelligencer/article/coronavirus-lab-escape-theory.html?utm_source=tw&utm_medium=s1&utm_campaign=nymasked about this

        This article is grossly misleading. I researched this stuff about six months ago, but haven’t retained complete references. If you want to know what to trust, look up primary sources of information using Google scholar and full texts of government documents. Especially when dealing with sensational subjects! One useful phrase is “gain of function” “pathogen”. The link below MAY be the first article alerting the scientific community to the unnecessary danger posed by these experiments:

        https://doi.org/10.1371/journal.pmed.1001646

        “From the conservative estimate of the rate of laboratory-associated infections of two per 1,000 laboratory-years [3],[16], it follows that a moderate research program of ten laboratories at US BSL3 standards for a decade would run a nearly 20% risk of resulting in at least one laboratory-acquired infection, which, in turn, may initiate a chain of transmission. The probability that a laboratory-acquired influenza infection would lead to extensive spread has been estimated to be at least 10% [19]”.

        The Wuhan lab is BSL4, safer than BSL3. The odds of an accidental release from this lab in October or November 2019 are minuscule. If I understand correctly, the cumulative risk from many labs doing such experiments over a long period of time prompted the NIH to shut down all gain of function experiments in potentially pandemic pathogens for almost three years. The National Academic of Science/NRC held workshops, did a full study of the risks and benefits, and published a book/online resource on the subject and the NIH ended the pause in such experiments in 2017.

        https://books.google.com/books?hl=en&lr=&id=QJ__CAAAQBAJ&oi=fnd&pg=PT14&dq=danger+of+gain+of+function+pathogen+studies&ots=PktaZAjjEk&sig=ijisxLz99M75JwSYsOZzEFWMuCA#v=onepage&q=danger%20of%20gain%20of%20function%20pathogen%20studies&f=false

        China did have problems with two accidental release of SARS-CoV-1 from labs around 2005, and publicized them to publicly punish those responsible. Personnel from the US Embassy visited the new BSL4 lab after it opened and sent a report, which was quoted out of context by many. The full text of that report is now mostly available. The biggest concern was that the Chinese government didn’t want to authorize working with the kind of dangerous pathogens the facility was built to study. They were being too cautious and holding back science, which is not surprising given the accidental releases made a decade earlier.

        https://www.washingtonpost.com/context/read-the-state-department-cable-that-launched-claims-that-coronavirus-escaped-from-chinese-lab/2b80aef2-f728-4c36-8875-3bf6aae1d272/?itid=lk_interstitial_manual_12

        For a rational discussion of origins of SARS-CoV-2, see the link below, which dismisses genetic engineering. Others disagree, but I don’t claim to have read them all. China-bashing is popular. If others don’t discuss and refute the rational in this article, I’d dismiss them. Somewhere there is also an official consensus statement from the US Intelligence Community (based on the experts they consulted) claiming SARS-CoV-2 wasn’t genetically engineered, but others in the Trump administration find China bashing career-enhancing. Also from WHO.

        https://www.nature.com/articles/s41591-020-0820-9

        IMO, China’s secrecy tell us nothing. China releases information when it helps the Communist Party and hides anything that could hurt the party. If the Wuhan Seafood Market and the (live) wild animal trade played any role in the origins of this pandemic, the Chinese government will be guilty of extreme negligence in not suppressing the (live) wild animal trade. The SARS-CoV-1 outbreaks involved the (live) wild animal trade, the danger was well known, and the Communist Party didn’t end it. So IMO they destroyed all of the animals at Seafood Market and sanitized it to ensure that no one could prove whether or not that market played a role. I don’t think the government knew whether or not that market played a role. Protecting the Communist Party from public accountability is more important than trying to find out the truth. If SARS-CoV-2 escaped from a virology lab or was part of a biowarfare program, the Chinese government isn’t going to tell us the truth about that either. We can draw no reliable conclusions from Chinese secrecy, but we can use their secrecy to make them look bad. (The above paragraph is merely opinion.)

        Every other viral pandemic in history has originated or passed through animals that live close to man. Given that you accept that COVID could have traveled from bat-infested Southern China to Wuhan without being detected, there are no inconsistencies in the theory it originated where expected, and someday we will find a close ancestor of SARS-CoV-2 in the wild. The existence of one viable theory doesn’t mean alternative theories aren’t possible, it just means they aren’t necessary to explain what happened. (If one wanted to theorize that SARS-CoV-2 originated in bats in the vicinity of Wuhan, that theory would be problematic because there aren’t many bats around Wuhan.)

        While the Chinese military is certainly conducting defensive biological warfare programs and may or may not be conducting offensive programs, they are doing it at some secret location that US Embassy personnel never visit. The people doing that research do not collaborate with Westerner and sometimes receive funding from them. In other words, the Wuhan institute and Shi were not involved (IMO)

    • Ron, I share your difficulty in working out exactly how it occurs. But I haven’t found any holes in the analysis in the van Dorp et al Nature paper that concludes no mutation that has arisen at least 3 times, including spike gene mutation D614G (at position 23403), causes significantly increased transmissibility.

      • One explanation I can think of for a variants to dominate without being more infectious is that mutability might not be uniform across the virus’s genome. In other words, there could be genetic factors that favor stability in certain random base pair structures over others even though these factors do not affect the transmissibility. One way to prove this would be to find instances of variants arising independently, not because of lineage. The logical driver would be genetic stability.

      • The “right” way to find out if and why this new variant is more transmissible is in a laboratory, not the field. 1) You an add an equal mixture of two viruses to a cell culture experiment and see if one virus gets into cells and replicates faster. 2) If you allow the viruses to bind, but wash they away before most enter, you can tell if one virus binds more tightly or enters more quickly than the other. 3) You can also see if one virus replicates to much higher levels than another.

        Some viral proteins are involved in suppressing the initial innate immune system response to infection. Does one strain reproducibly induce lower levels of interferon in patients or perhaps animal models? Other none structural proteins are transported into the nucleus and shut down normal cellular process that resist takeover of a cell by a virus. The key mutations that make a strain more transmissible by this mechanism obviously will be found in these other viral proteins (non-structural proteins), not the spike protein.

        If important differences between two strains aren’t found in the above assays, then one might expect both strains to produce similarly high levels of viral load in patients, though I have the impression that repeated swabs don’t give very tight data on viral load. If both viruses replicate equally well, then they could differ in the ability to get out of the patient as droplets or aerosols. Coughing and runny noses are great mechanisms for getting out of one patient and infecting another. A strain that produces more severe coughing or sneezing would have a transmission advantage.

        Finally, there is the mystery of what makes a super-spreader? Obviously if a viral strain makes it more likely a victim will be a super-spreader, it will be more transmissible. Without knowing what makes a super spreader, further speculation is worthless.

        Epidemiologists are looking at the end result of an extremely complicate process with complicated mixture of variants and mutations. In the lab, one can investigated individual steps in this complicated process and perhaps pinpoint what is different.

        Scientists find that pig and fowl farmers are frequently asymptomatically infected with novel strains of swine or avian flu. Those strains aren’t well adapted enough to growing in human cells to high enough viral titer to have a decent chance of being transmitted by droplets or aerosols from one human to another. The mostly likely way a virus becomes more transmissible is probably its ability to replicate more efficiently inside patients.

      • Frank, thanks for your inciteful comment. I would also combine your points to expand your conclusion that transmissibility is the product of all these factors, cell binding, immune suppression or evasion, replication efficiency, producing the highest viral load to the least amount of symptoms that would prevent that host from interacting with others.

        Evolutionary forces thus drive the virus to be less and less incapacitating but more and more infectious to the host species. This is why most viruses can’t jump and propagate in the non-host species, but if they do they are usually more harmful. That NIH scientists felt that making lab chimera bat-human viruses was too dangerous to do in the USA but fine to fund Chinese research was nuts.

      • Ron wrote: I would also combine your points to expand your conclusion that transmissibility is the product of all these factors, cell binding, immune suppression or evasion, replication efficiency, producing the highest viral load to the least amount of symptoms that would prevent that host from interacting with others.

        However – if there are significant differences between strains – they are due to one discrete mutation. Combinations of mutations aren’t necessarily passed on, most strains die out when they aren’t passed on. Remember, most infected patients infect no one else and their variant dies out. Super-spreaders do most of the transmission and most “survival of the fittest” is mediated only through a small fraction of the population. My brain is struggling with this concept.

        The video linked by Joshua below explains is a more authoritative and sophisticated summary of what I was trying to communicate.

        https://judithcurry.com/2020/12/29/the-relative-infectivity-of-the-new-uk-variant-of-sars-cov-2/#comment-937851

      • Frank –

        I would note that virologists caution about using the term “strain”

  5. Nic, thanks.

    I do take a bit of issue with: “does not currently appear to represent a serious increase in the menace posed by SARS-CoV-2, even in the worst case that its higher observed growth rate is entirely due to increased transmissibility.”

    With some areas in the US (and other countries) hovering close to hospital saturation, it would take little increase in transmissibility to push them over the threshold, substantially increasing the CFR (and also deaths from denied medical care for non-COVID patients).

    • mesocyclone

      If you look at this link you will see within the article some very useful charts, one of cases per day and one of deaths per day

      https://www.dailymail.co.uk/news/article-9095269/England-needs-national-lockdown-prevent-catastrophe-January-February-SAGE-warns.html

      We should by now be seeing a sharp upturn in deaths in response to more cases from 2 or so weeks ago. That will help determine if the new variant is not only more easily caught, but that it causes deaths at the same rate as the previous version, or whether whilst being easier to catch it is not as deadly

      tonyb

    • mesocyclone, I was thinking in a UK context, and more in terms of how much more difficult it would be in terms of required measures to keep Rt down to 1 ,given the new variant, than what the effect on hospital availability would be if no further measures had been or were imposed in response.

      • “I was thinking in a UK context, and more in terms of how much more difficult it would be in terms of required measures to keep Rt down to 1 ,given the new variant, than what the effect on hospital availability would be if no further measures had been or were imposed in response.”

        Thanks, understood.

        I’ve seen a narrative developing in the media along the lines of “more transmissible but not more deadly, nothing to see here, don’t be alarmed,…” That concerns me, and it seems to be encouraged by some in the medical community.

        It will be interesting to see what we learn about the actual change in Rt as a result of this or other variants. Although, I guess strictly speaking, it’s a change in R0 that reflects in Rt. Of course, R0 can’t be measured at this point, and changes in Rt due to transmissibility changes are hard to disentangle from changes in behavior.

    • “With some areas in the US (and other countries) hovering close to hospital saturation, it would take little increase in transmissibility to push them over the threshold”

      I don’t know the situation in the US, but in the UK the increased Covid load on hospitals in the current ‘wave’ is largely a result of different admission criteria; hence, for example, the much higher survival rate (better treatment is a factor, but is not a sufficient explanation). During the first wave in April the fear that hospitals would shortly be overwhelmed meant that hospital managers were not allowing admissions unless you were already critically ill. The largest proportion of cases at that time were in care homes, where by-and-large they were left to cope as best they could.

      Certainly in the UK, hospital and ICU occupation for respiratory problems are at normal levels for the time of year despite Covid. The NHS always has a “winter crisis” and this winter is no different. Normally, influenza is identified as the big killer. This year it appears to have been displaced by Covid. One theory is that public health measures put in place for Covid have reduced the spread of the ‘flu’, thereby reducing those numbers. Hopefully that is the case, rather than people who would otherwise die from influenza simply being killed by Covid instead.

      • Certainly in the US, COVID mitigation measures have dramatically reduced influenza.

        The hospital statistics I follow the most closely are for Arizona, which at the moment is one of the worst states in terms of positive tests per capita. Our hospitals and ICU’s are over 50% COVID19, with well under 10% of capacity left. This is in spite of the fact that they are limiting some normal hospital care, and people are avoiding tests and procedures on their own because they don’t want to be exposed.

        This means that it wouldn’t take a large rise in cases to create a crisis. In fact, our November rate of increase had the universities forecasting a hospital crisis by Christmas, with people being denied necessary care – triaged to die. That didn’t happen – yet – because our rate of positive cases has plateaued. But… hospitalizations are still rising, and the only reason the ICU’s aren’t overloaded (state wide – some are full) is because the number of non-COVID19 cases is declining. I presume that is due to postponed care. In other words, they are using up the margin.

        Today:
        59% – ICU usage for COVID19
        32% – ICU usage for non-COVID19
        9% – ICU availability

        Contrast this to early October:
        7% – ICU usage for COVID19
        71% – ICU usage for non-COVD19
        22% – ICU availability

  6. Instructive too, the reaction to the news of the supposed increased virulence of the UK strain when we learn not long after that the strain is already everywhere and has been for a while along with a hundred others which we learn is totally expected based on how all viruses behave…

  7. This is the simplistic narrative that we are up against:

    “Climate experts are not being listened to despite the coronavirus pandemic highlighting the importance of following science, the environmental activist Greta Thunberg has said.”

    https://amp.theguardian.com/environment/2020/dec/29/we-cannot-make-it-without-science-greta-thunberg-says-climate-experts-are-being-ignored

  8. Matthew R Marler

    Nic Lewis, thank you for the essay and responses to comments.

  9. Nic Lewis – thanks for all your investigation and detailed explanation. If the new strain is no more transmissible/infective than other strains, would it be correct to say that the newly increasing (‘second wave’) numbers would be about the same regardless of the existence of a new strain?

    You say “Confident claims by the UK government scientific advisers that the higher growth of B.1.1.7 is due to increased transmissibility are misplaced; it could be partly of wholly due to other factors”. There is a suggestion of what those ‘other factors’ might be for another variant – “resumption of travel across Europe, and lack of effective screening and containment may explain the variant’s success”. Do you have any idea what the ‘other factors’ might be for B.1.1.7 in the UK? [if you did in fact say what they might be then I missed it]

    • Mike Jonas – I’m afraid that I don’t know what ‘other factors’ might explain the rapid growth of B.1.1.7. And I’m not saying that it necessarily is due to other factors. Rather, I’m pointing out that, since other variants have achieved similar success but are now thought not to be significantly more infective, it is wrong for NERVTAG to make a ‘high confidence’ finding that B.1.1.7 is substantially more transmissible.
      The contact tracing analysis published by PHE since I finalised my article is more direct evidence that is suggestive of B.1.1.7 actually being more transmissible, but differential geographic growth or some other factor may account for at least part of the contact attack rate difference found.

  10. According to the latest PHE report (https://bit.ly/3aThMAX), infectivity of the new variant compared to the old based on Test & Trace data is 15% versus 10% (proportion of those identified as having being exposed who subsequently go on to test positive). There is no distribution data so it’s not possible to see whether there are any differences in the pattern of spread.

    • Yes, I’ve seen that too. It’s a great pity that no regional breakdown is given.

      • Also missing is a breakdown of the people/households the spread comes from. I’d like to know whether the averages reflect the typical pattern, or whether there is wide variability. Contrasting these patterns between the two Covid variants would also be interesting, and would certainly be useful to know when considering policy.

      • Joe - the non epidemiologist

        Aporiaci1960 comment – “Also missing is a breakdown of the people/households the spread comes from. ”

        That is a valid question, ie where are the environments where covid is actually spread. Absent the areas where there is a complete hard lockdown, the mitigation efforts seem to have only minor effects on the trajectory of the viral spread. .

    • According to ONS user-requested modelling of development of the new variant’s prevalence relative to that of other variants by region (https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/adhocs/12708covid19infectionsurveyorf1abnpositivityrates), the advantage in weekly growth of the new variant from 9 November to 18 December varied between 1.12 and 1.58, with an average for England of 1.49. (The proxy used is less reliable prior to mid-November.)
      This daily data is for prevalence not incidence, so represents some sort of moving average of incidence over the last 10-14 days or so.
      It’s not obvious what would account for such widely varying regional growth rate advantages. The ONS modelling could be wrong, of course.
      The advantage in weekly growth of the new variant correlated quite strongly both with its prevalence on 9 November (r=0.56) and with the log growth rate since then in the non-variant prevalence (r=0.69). Not sure why that should be the case.

  11. Pingback: Latest News – Lockdown Sceptics

  12. Pingback: Lockdown sceptics:Fact Check Fail;“If The New COVID-19 Strain is More Transmissible, Why Isn’t It Taking Over in Every Region?” – naufrage/sauvetage

  13. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 – Watts Up With That?

  14. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 – Climate- Science.press

  15. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 |

  16. In the UK intensive care wards are again being overwhelmed with covid19 patients as in the spring.
    Therefore stronger quarantine and lockdown measures are needed, it doesn’t matter what the R numbers are or the details of the virus strains.

    • Phil

      The fact that we are on our third lockdown should surely suggest they don’t work? Intensive care wards are overwhelmed EVERY winter and patients treated in corridors when there is a serious flu outbreak.

      We have far too few beds per 1000 of population and take no account of the rapidly rising and ageing population.

      tonyb

      • Geoff Sherrington

        climatereason.
        In Australia many people think that lockdowns work and much as they are disliked, we have next to zero cases week after week. Tight control of movement and rapid, deep contact tracing with quarantine are, for now, showing how one outburst (State of Victoria, last half of 2020) can be reduced and for the other States, held to near zero. Like under 10 new cases a day for populations of 10 million or so.
        Though, one does wonder how long the discipline will be effective when other countries have got Covid so widespread.

    • Joe - the non epidemiologist

      Phil’s comment – “In the UK intensive care wards are again being overwhelmed with covid19 patients as in the spring.”

      Your data point lacks context. A full comparison will shed some light on your statement.

      for the period 2016 through 2018 –
      What was the total # of ICU beds by month
      What was the usage of ICU beds by month
      What is the # of unused beds by month.
      what is the total bed capacity and usage by month
      How much of the change is seasonal,

      Without context, your statement is meaningless and typical of the followers of Covid-19 Freakout science.

      Thanks

    • I don’t think that’s true. They weren’t overwhelmed in the spring, for a start. And I’ve read that just before Christmas hospitals in England had fewer Covid patients, and fewer of them in ICU units, than in the spring, apart from in the South East and the East of England regions. Show me data to back up your claims, or will regard them as NHS etc. propaganda.
      And the NHS a) should have more ICU capacity now, as they knew a 2nd wave might be coming and they’ve had 6 months to boost capacity; and b) doesn’t need as many ICU beds per COVID patient now as (i) they’ve got better drug treatment to avoid cases become very severe and (ii) ICU is usually only really needed for Covid patients who are being mechanically ventilated, and a far lower proportion of them are being ventilated now than in the spring (in many cases it has been found harmful to do so).

      • Nic

        You don’t need to have too long a memory to see that uk hospitals were overwhelmed in 2018 This time with an Australian mutant variation of flu. Depressingly familiar especially as it says it thought the 2017 season was the worst ever for overcrowding. so that is 2 years in a row,

        https://www.dailymail.co.uk/news/article-5229733/Thousands-NHS-operations-cancelled-winter.html

        Tonyb

      • Tonyb
        Agreed, although it depends on what one means by ‘overwhelmed’. NHS hospitals often operate very near no nominal capacity limits in the winter and I’m not sure that everyone would regard cancelling some tens of thousands of non-urgent operations as being ‘overwhelmed’.

      • “I’m not sure that everyone would regard cancelling some tens of thousands of non-urgent operations as being ‘overwhelmed’.”

        While one can object to “overwhelmed” – it is certainly a serious situation when such measures are undertaken. BTW, here in Arizona, the largest hospital chain announced the cancellation of all non-urgent procedures as of today.

  17. https://zeynep.substack.com/p/a-counter-argument-against-public

    (trigger warning, some criticism of rightwing weaponization of uncertainty at the above link)

    But more to the point:

    -snip-
    …the well-known virologist Vincent Raccaniello disagrees with epidemiologists that epidemiological data is high quality evidence for the novel phenotypic traits in the worrisome SARS-CoV-2 variant being tracked in the UK.
    -snip-

  18. A beacon of light at the end of the tunnel:

    Oxford University/AstraZeneca COVID-19 vaccine approved

    https://www.gov.uk/government/news/oxford-universityastrazeneca-covid-19-vaccine-approved

    The fresh veg at my local Lidl were noticeably sparse and shelves emptier than usual today. It’s a trend that I expect to continue. No doubt, there’ll be something to eat, just not necessarily what you’re used to.

    • Alan

      Our local fruit and veg shelves are bulging. Perhaps you are in one of those areas where transport is difficult due to snow? Or perhaps it’s just people stocking up ready for new years eve? People went completely mad with food buying for Christmas especially bearing in mind the supermarkets were only shut on the day itself.

      Tonyb

      • I’m in the south east with no snow. I hope I’m wrong but it’s happened before in this store – panic buying. I might have to get there early in the morning to get what I want. I’ll let you know come January.

  19. UK government declares new variant emergency lockdown measures:

  20. it is like a gas rushing into a vacuum! the strain is spreading because of bad behavior into populations that are naive to the virus.

    public health guidelines still defeat the virus.

    • It is amusing to see so many intellectuals discovering all of a sudden that things like viruses exist and that they mutate!

      And also the fact people die. In most parts of the world 80 year olds dying are celebrated with feasts.

    • It seems there are many countries that haven’t defeated the virus. Governments solves all kinds of problems. Poverty, housing, education.

  21. We’ll never know the hours that the Left doubtless invested, trying to link the virulence of civid19 to CO2

  22. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 | awarecitizen.com

  23. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 ⋆ 10ztalk viral news aggregator

  24. Pingback: The relative infectivity of the new UK variant of SARS-CoV-2 | altnews.org

  25. Katie Hopkins makes a good case saying MSM is spreading unnecessary fear about hospitals filling up with covid patients when in reality number of available critical beds is reduced due to self-isolating staff:

  26. “she acts as if the increased spread and healthcare workers isolating at home could be decoupled. That’s nuts.”
    Nonsense. Testing NHS staff who would otherwise be at home isolating with a rapid lateral flow test before work, every day (or maybe even every two days) would ensure that they were most unlikely to be infectious (even if they would be positive by PCR test).

    • Note that the NHS has an incredibly high sickness absence rate even excluding COVID related absence. About 4% overall, and 6% for Hotel, property & estates staff! Much of it is ‘psychiatric’ illness. Maybe this is typical for a public sector organisation; it would be highly abnormal elsewhere, I would have thought.

    • The PCR testing regime is far from perfect. If I’m not mistaken, I was the first person in these threads to loudly promote antigen testing as a public health surveillance (rather than treatment) methodology.

      Nonetheless, everywhere, the ebb and flow of positive PCR tests has been followed by a proportional ebb and flow in hospitalizatons, ICU admissions, and deaths.

      You have tried to trot out this “nonsense” before and it’s quite remarkable that you haven’t learned the lesson yet. You tried it with Sweden and failed miserably. Do you remember when you tried to dismiss the spike in positive tests as a blip?. More then once. And wrongly tried explain away significance of the spike in positive tests by effectively ignoring the consistent lag between testing outcomes and trends in morbidity and mortality?

      It isn’t just you. We’ve been hearing this nonsense about decoupling spikes in positive PCR tests from corresponding spikes in morbidity and mortality since early summer in the US. But predictably, the following corresponding spikes in hospitalizations, ICU admissions, and deaths did not diminish in the least the inane babbling about how positive PCR tests are irrelevant. The “nonsense” about the “casedemic” continues unabated.

    • You see what Joshua is doing here is what he always does. He tries to make a general point with no data supporting it and no statistical analysis. Just psuedo-science. It would be pathetic if he wasn’t also easily proven to be wrong. Positive tests do not correlate well universally with hospitalizations and deaths. A counterexample is New York now and New York in March and April. Positive tests are 25% higher now yet deaths are a factor of 8 lower. Compare Germany and the UK. There is no universal valid relationship here because positive tests are a strong function of the number of tests performed which is strongly dependent on having a big surplus of test kits.

      Further is later comments, Josh the house cat, tries to attack the elephant’s ankles by claiming that PFR’s are now higher than Willis predicted this summer. But everyone has been way off about this pandemic and Josh has given no predictions at all. He lacks the scientific and statistical knowledge to make a credible prediction. Why is Joshua showing up here to bite the ankles of his scientific betters? Because this is the only venue where he is allowed to post such nonsense and not get moderated.

  27. If the estimated logarithmic rate of decline in weekly COVID-19 deaths in Sweden seen over the last six weeks continues, only about 1,100 further deaths would occur. That would bring total deaths up to approximately 6,400, or 0.06% of the total population. Of the first 4,500 deaths, some 40% involved people living in care homes,[16] a slightly lower proportion than earlier in the epidemic. To date, the average age at death was 82, and in only 6% of cases did a death not involve a co-morbidity (other health condition).

    Conclusions

    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.

    In the absence of a change in trends, it seems likely that the epidemic will peter out after a thousand or so more deaths, implying an overall infection fatality rate of 0.06% of the population (0.04% excluding COVID-19 deaths of people in care homes). This is broadly comparable to excess deaths from influenza infections over two successive above-average seasons, such as 2016–17 plus 2017–18.[17]

    The absence of a lockdown order, with the government largely trusting people to make their own individual decisions regarding their behaviour, informed by their particular circumstances, has enabled life to continue with less disruption and reduction of people’s autonomy in Sweden than in most other western European countries. While this has also meant that COVID-19 deaths to date have been higher than in some (but not all) other countries in which a lockdown was imposed, the wider spread of the epidemic in Sweden means that the future COVID-19 outlook there is better.

    The herd immunity threshold is likely lower at present than it would be if people were behaving completely normally; it may also be seasonally lower. However, the continuing spread of infections since the peak of the epidemic, particularly among young people, should provide some margin of safety against its resurging when behaviour returns closer to normal and summer ends. That is, there is less risk of a second wave of the epidemic next winter. And if a second wave occurs, fewer measures should be needed to control it than in other countries.

    The only question at this point is just how far off your speculation was.

    What’s settled is that (1) you were way off, (2) you won’t acknowledge your errors, (3) will continue to double down on the same thinking that led to your errors (which is what happens when people don’t accept accountability for their errors).

    It’s not the making of errors that’s the problem. Creating toy models to simulate an incredibly complex reality with so many unknowns is bound to generate errors. I respect the skills involved in doing such modeling. I consider the attempts at the modeling to be important and I think that experimenting with the parameters is likewise important.

    The problem is (1) when the errors result from a disrespect for uncertainties as we had here and, (2) people duck accountability for their errors.

    • More flim flam artistry from Joshua. Everyone knows (except Josh the pseudo-scientist) that herd immunity levels will be a strong function of the seasons for example as always happens with the flu. Herd immunity was likely reached this summer in many places. Then we had winter and people stayed indoors and in close contact with other people and R went up significantly.

      For the record, Ferguson and our own CDC were dramatically wrong in their predictions of the course of this epidemic.

      • dpy6629: I respectfully suggest you look at real data somewhere. There were a trivial number of cumulative cases in North Dakota before September. By Thanksgiving, more than 10% of the total population had tested positive. (We don’t know how many people had mild or asymptomatic infections, but the early seropositivity studies suggested PCR testing was missing 6 to 15 cases for ever case detected. That lead to a low IRF and the mistaken claim that COVID is no more deadly that influenza.) Today ND’s cumulative cases amount to 12% of the population (14% in Bismarck), but the number of new cases has dropped dramatically. We don’t if approaching herd immunity played a role in suppressing the pandemic in ND or if fear or policy suppressed the pandemic. (ND hospitals reached “100% of capacity” in early November, so fear and restrictions could have been responsible for slowing.)

        Given the situation in ND, it is ludicrous to suggest the anywhere in the US reached herd immunity this summer with half as many cumulative cases as ND has today. For example, the pandemic is rebounding in NJ, which was badly hit this spring.

        Furthermore, herd immunity doesn’t vary with the season. Herd immunity means that no pandemic can grow exponential under “normal conditions” at any time of the year.

      • “Today ND’s cumulative cases amount to 12% of the population (14% in Bismarck), but the number of new cases has dropped dramatically. We don’t if approaching herd immunity played a role in suppressing the pandemic in ND or if fear or policy suppressed the pandemic. ”

        I think SD is more interesting, because there were very few mandates, and they took place early in the epidemic yet SD’s epidemic didn’t really take off until months later. And then it peaked and subsided.

        I suspect, but don’t know, that immunity played a significant factor, since one could reasonably project that over 50% of the population had the infection. But… a very important point that people keep ignoring… whether or not a government imposes mandates, many people will change their behavior in ways that reduce the spread of the disease. And, it is very hard to tease those changes out. You can look at mobility and guess at some of it. But the rest?

      • Comment deleted as it duplicates the author’s next comment

      • Dagnabbit!

        Lol. Is the population fatality rate “seasonal” also?

        Gomes says that a population can cross back and forth over a herd immunity threshold seasonally.

        But Nic reverse engineered from rate of infections 8 MONTHS ago to conclude that Sweden had reached a herd immunity threshold under more or less normal behavioral conditions. He posted pictures of young people partying in bars to say that some 10% or so of Swedes having been infected meant that under normal behaviors someone there who had never been infected would be unlikely to encounter someone who is infectious. Did he ever say, in the hundreds of words he wrote on the topic, that of course, it was quite likely thay when the season changed, the rate of identified infections would increase many-fold (depending on the acquisition rate) and people would start dying again at rates approaching the rate they had at the peak of the first wave?

        Well, lessee:

        That is, there is less risk of a second wave of the epidemic next winter. And if a second wave occurs, fewer measures should be needed to control it than in other countries.

        Well, nope!

        He even went so far as to say that herd immunity status would predict relatively few deaths going forward before the pandemic “peter[ed] out.”

        Is the pandemic pestering out a “seasonal” phenomenon also? Lol.

        Nic was wrong. He looked at some curves on a computer screen and thought they told him about the complexities of human biology and human behavior under *highly uncertain* circumstances. He disrespected unvertstinty, such as the potential that a *seasonal effect* in Sweden was maybe due in part to people traveling to vacation. homes for the summer?

        How do we know that? Well, by his erroneous projections about population fatality for one.

        It’s right there on your computer screen.

        But even more so, and more dangerously, because he tried to extrapolate from the temporarily low infection rate in Sweden to suggest that other countries follow Sweden’s policies even though in those other countries large populations wouldn’t be hanging out in summer homes in incredibly sparsely populated areas (or working from home at similar rates, or living in such small household sizes, etc.)

        “Herd Immunity” in the popular vernacular has come to mean that enough people have become infected and recovered or died that people can return to normal behaviors without it being lokely that they’ll encounter an active virus at levels likely to make them ill or die. And that the pandemic will “peter out” and not just temporarily slow down only to come back at a similar or possibly even accelerated rate in a different season.

        We have plenty of indicators that’s what Nic meant. But if it isn’t what he meant then it’s even worse, because that would mean he knowingly and misleadingly suggested that the pandemic would “peter out” and that people would no longer be getting sick and/or dying in the future at concerning rates if they went back to normal behaviors, even those in countries where the behaviors were VASTLY different than behaviors were in Sweden at the time. No, it would mean that he knowingly and misleafingly WRONGLY low-balled the number of Swedes who would die going forward.

        I don’t know Nic, but I doubt he’d do something like that. I’d rather think he just messed up due to under-estimating uncertainty. Lots o’ people do that. It happens.

        Did he, in fact, warn people NOT to over-interpret the temporary trends in Sweden to think that their having crossed a theoretical “herd immunity threshold” would suggest the pandemic had “peter[ed] out?”

        I’ll let you be the judge.

      • “More flim flam artistry from Joshua. Everyone knows (except Josh the pseudo-scientist) that herd immunity levels will be a strong function of the seasons for example as always happens with the flu. Herd immunity was likely reached this summer in many places. Then we had winter and people stayed indoors and in close contact with other people and R went up significantly.”

        Speaking of film-flam, your use of “herd immunity” is nonsense.

        Herd immunity is not a function of the seasons. It is true that an epidemic can run out of steam because of social distancing (related to seasons), but that really is not herd immunity. Yes, immunity might be a contributing factor – it has the exact same effect as lowing Rt. But it is not “herd immunity.”

        But Joshua’s use of the term “logarithmic” is very wrong. But then, he is not a math person. “Exponential” is closer to right. The trend, whether going up *or* down is exponential (or close to it – if immunity is changing, it diverges from exponential to some extent).

      • > But Joshua’s use of the term “logarithmic” is very wrong. But then, he is not a math person. “Exponential” is closer to right. The trend, whether going up *or* down is exponential (or close to it – if immunity is changing, it diverges from exponential to some extent).

        Logarithmic? When is my “very wrong” use of the term “logarithmic?”

        Are you referring to when I was quoting Nic’s use of the term?

      • meso –

        > Herd immunity is not a function of the seasons.

        The conceptualization that herd immunity is a function of seasons brings an example to mind for me.

        Suppose 100 people shipwrecked on an island. When they hit the island one person was sick and that person infected 2 other people and then those 3 people together then infected 7 more total (IOW, on average each infected person then infected more than 1 other person ).

        And as soon as those 10 got sick everyone quarantined and after 1 month no new illnesses surfaced.

        90 people never developed antibodies because they were never infected. Would we say that the population of the island had reached herd immunity even though only 10% were ever infected?

        One more infected person traveling to the island could easily spark exponential growth of the virus and so it seems to me it wouldn’t be very useful to characterize the island’s population as having reached “herd immunity”.

        Yet that seems to be the equivalent functional definition that some of our friends are working from. It’s rather like saying that to reach herd immunity all we need to do is lock everyone up in isolation. Yet that’s exactly the kind of thinking they then turn around and say would delay the achievement of “herd immunity.” There doesn’t seem to be a consistent logic.

        When public health officials are talking about the need to have 75%+, or 50+ plus infections/vaccinations to reach “herd immunity,” they’re not talking about a rate that would easily explode again if there were relatively small changes in behavior. They’re talking about reaching a point where the likelihood of getting infected would be relatively small under normal behavior conditions.

      • I thought this article was pretty good:

        https://www.nature.com/articles/s41577-020-00451-5

      • Well Frank, I didn’t say that everywhere in the US reached herd immunity in the summer, just that many places may have. The point I was making is that Nic’s analysis may indeed have been correct on this score. I don’t know about North Dakota. I think places like New Jersey, New York and Pennsylvania are seeing a second wave. Since all have had strong restrictions in place since March, the only logical explanation is that they did indeed reach effective herd immunity (given their restrictions) in the summer when the epidemic almost died out. But with winter time R has increased so that there is a second wave and herd immunity fraction has gone up.

        If you have an alternative explanation I’d entertain it but my explanation I think readily explains most the course of the epidemic in states that were hard hit early.

      • ” Since all have had strong restrictions in place since March, the only logical explanation is that they did indeed reach effective herd immunity (given their restrictions) in the summer when the epidemic almost died out. But with winter time R has increased so that there is a second wave and herd immunity fraction has gone up. ”

        You are abusing the term “herd immunity.” Qualifying it with “effective” doesn’t change that. You don’t know if immunity was a factor or not – only that the curve reversed itself. But, that can happen without any immunity at all.

      • The herd immunity threshold is not some kind of universal constant. It depends on R the rate of transmission and that can vary strongly with the season, people’s behaviors, etc.

      • Meso, Do you have an alternative explanation for why with essentially the same restrictions in place the whole time, the epidemic almost died out this summer and then a second wave developed this winter in the states I mentioned?

      • “The herd immunity threshold is not some kind of universal constant. It depends on R the rate of transmission and that can vary strongly with the season, people’s behaviors, etc.”

        That is incorrect. It is a constant of the disease, and is only meaningful in conditions where behavior is normal. Any other usage is unusual, and potentially very confusing. I suppose one could modify it a bit for different localities – where factors like humidity might be different. But, modifying it for hard to measure behavioral impacts is a bridge too far, and becomes tautological.

        It is true that a combination of immunity and behavior can result in Rt < 1.0 during the epidemic, but that is not "herd immunity" and the HIT has not been reached. It is also true that behavior changes alone can produce that same change to Rt. In fact, it is nearly impossible to disentangle immunity and behavior changes, unless you actually know how much immunity is out there.

        "Do you have an alternative explanation for why with essentially the same restrictions in place the whole time, the epidemic almost died out this summer and then a second wave developed this winter in the states I mentioned?"

        Alternative to what? A misuse of the term "herd immunity" and "herd immunity threshold?"

        If the epidemic died out and then reappeared in the same population, it is solid proof that herd immunity was never reached.

        As to why we have a second wave now, I am not sure. Some of it is certainly behavior – note that the presence or absence of government mandates is hardly a determinate of behavior. It is also possible that we already have enough of new strains with higher R0 to be a big factor, although I am certainly not confident of that. Another factor could be environmental – humidity changes, etc. But, you have to look at it one locality at a time, since environments and behavior vary substantially.

        Living in the Phoenix, AZ area, I am in a place where people are more outdoors during the winter, and more indoors during the summer. And yet, we had a huge peak in early July, and are now in the middle of an even bigger one at year end. So… did immunity cause the end of the July peak, and if so, why are things so much worse now?

        The best evidence is that the level of immunity in the population here was too low to turn the epic-curve around – and that includes random antibody sampling by CDC of our population (including my zip code) soon enough after the July peak that the antibodies should have still been detectable.

        You can generate good graphics of Arizona data at 91-divoc dot com.

      • Yeah – “Effective herd immunity.” I love that.

        I’ve seen that before. It’s like they would reach “effective herd immunity” on the island in my example here:

        https://judithcurry.com/2020/12/29/the-relative-infectivity-of-the-new-uk-variant-of-sars-cov-2/#comment-938095

        Which means not herd immunity at all, but a convenient way to say it’s herd immunity because of a lower rate of transmission because of circumstances that have nothing to do with herd immunity. So you don’t have to admit you’re wrong.

      • > Meso, Do you have an alternative explanation for why with essentially the same restrictions in place the whole time, the epidemic almost died out this summer and then a second wave developed this winter in the states I mentioned?

        Behaviors changed.

        When you’re saying “effective herd immunity” what you’re saying is that behaviors changed.

        It’s not herd immunity in any meaningful sense.

      • meso –

        Are you going to explain where you found my ‘very wrong” use of the term “logarithmic”?

      • No. I lost the context and it isn’t worth digging back up.

        Generally, if logarithmic is used to refer to the rate of increase or decline, it is incorrect. But in some technical discussions, logarithms are used – for example, viral loads.

      • Yah, well, didn’t happen actually.

        I think you were reading a section where I was quoting Nic (I used italics but didn’t specifically note I was quoting him). You might want to take it up with him. Of course, you could do a search for “logarithmic” on the page if you think that wasn’t it.

      • @dpy6629
        Re: “Since all have had strong restrictions in place since March, the only logical explanation is that they did indeed reach effective herd immunity (given their restrictions) in the summer when the epidemic almost died out. But with winter time R has increased so that there is a second wave and herd immunity fraction has gone up.”

        Herd immunity is about baseline conditions of R0 and thus, by definition, includes no additional behavior changes and no additional public health interventions above what would normally be present (i.e. conditions in the absence of the pandemic, such as during the same time of year in 2019). So you’re abusing the term “herd immunity” by re-defining it to apply under conditions of additional restrictions, i.e. additional public health interventions. It’s the same reason why Nic Lewis was wrong when he claimed Sweden, including Stockholm, reached herd immunity after additional restrictions. Even Gomes’ team tacitly admit this when they state the herd immunity threshold in terms of R0 (plus heterogeneity, where behavior changes and public health interventions are not examples of heterogeneity).

        “This quasi-equilibrium is maintained 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.pnas.org/content/117/51/32764

        “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

        “In the simplest model, the herd immunity threshold depends on the basic reproduction number (R0; the average number of persons infected by an infected person in a fully susceptible population) and is calculated as 1 − 1/R0 […].
        […]
        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

        “In idealized scenarios of vaccines delivered at random and individuals mixing at random, herd immunity thresholds are given by a simple formula (1 − R0) which, in the case of SARSCoV-2, suggests that 60-70% of the population would need be immunized to halt spread considering estimates of R0 between 2.5 and 3. A crucial caveat in exporting these calculations to immunization by natural infection is that natural infection does not occur at random.”
        https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v3.full
        [with: https://www.medrxiv.org/content/10.1101/2020.12.01.20242289v1.full ]

        JC SNIP. I will continue to use the SNIP any time you refer to me or Nic Lewis in a content-free insult.

        You can now return to saying usual catchphrases like ‘your reply has too many words for me to read!’.

    • As Joshua says, I wrote some months ago about Sweden:

      The herd immunity threshold is likely lower at present than it would be if people were behaving completely normally; it may also be seasonally lower. However, the continuing spread of infections since the peak of the epidemic, particularly among young people, should provide some margin of safety against its resurging when behaviour returns closer to normal and summer ends. That is, there is less risk of a second wave of the epidemic next winter. And if a second wave occurs, fewer measures should be needed to control it than in other countries.

      I accept that I underestimated – based on what I had read – just how seasonal COVID-19 would be. Greater infectiousness as colder autumn weather drew on appears to have raised the herd immunity threshold to above the existing level of population immunity. As a result of that, on top of an apparent gradual return during the summer to more normal social behaviour, particularly by young people, Rt rose from confortably below 1 to significantly above 1 – although to nowhere near the levels seen in the first few weeks of March – and infections rose substantially in October and November.

      Nevertheless, my caveated estimate of ~6,400 deaths caused by COVID-19 still looks fairly realistic. The best measure of such deaths is generally agreed to be excess mortality. Up to 6 December, excess deaths in 2020 (relative to the 2015-19 mean) appear to have been under 4,500 in Sweden (https://ourworldindata.org/excess-mortality-covid). Extrapolating recent trends suggests less than 5,500 excess deaths for 2020 as a whole. The epidemic isn’t over yet, of course, but COVID-19 cases and intensive care admissions show indications that the peak might now have been passed, although a further resurgence is of course possible.

      • ” Greater infectiousness as colder autumn weather drew on appears to have raised the herd immunity threshold to above the existing level of population immunity. ”

        How to you explain the current US peaks in Arizona and southern California? It isn’t cold in either place – in fact, here in Arizona, winter is when we spend *more* time outdoors. And yet, our hospitals are filling up – to the point the Banner Hospitals, our largest hospital system, now prohibits all non-emergency procedures.

        Also, I wish you wouldn’t use “herd immunity threshold” in such a conditional way. That really isn’t what it means. Yes, anything that causes the epidemic to turn around acts mathematically the same way as the herd immunity threshold – it lowers Rt below 1.0. But, we could have an almost completely immunologically naive population have a peak and then a turn-around, without ever having much immunity. In fact, that happened in last spring in the US in most states. When the case rates turned, the total number infected was a tiny percentage of the population – way under 10%. Immunity had little to do with that turn-around.

        Take a look at this graph, and tell me where immunity was a factor:

        http://91-divoc.com/pages/covid-visualization/

      • Trying to put the graph in as an image:

      • > Nevertheless, my caveated estimate of ~6,400 deaths caused by COVID-19 still looks fairly realistic. The best measure of such deaths is generally agreed to be excess mortality.

        This is the kind of dissembling that does your credibility no good

        You weren’t referring to “excess deaths” when you made your projection.

        Now you want to switch metrics because your estimation looks bad?

        Excess deaths as a metric has all kinds of complications and uncertainties as a way to measure COVID deaths, which is what you were estimating. But notice that you deal with none of them.

      • Joe - the non epidemiologist

        Nic – Steve McIntyre mentioned a textbook on his twitter feed in the May June time frame which discussed the historical trends and trajectory of influenza over the various regions of the world over the last 150+ years. Do you recall the name of the textbook or the author (boyles? maybe?)

      • Joe – I’m afraid not. Maybe searching Steve M’s twitter account feed would turn up what you are after.

      • There is no dissembling involved here Josh. A prediction can be wrong in one sense and not wrong in another. Nic is perfectly entitled to point this out. In any case, predictions in an epidemic should be treated with skepticism as the equations are ill-posed and outcomes are sensitive to parameter values.

        What I am seeing here is that your obsessive disorder has returned. It wasn’t funny when you did it to Judith and its not funny now either. You always seem to pick people who are vastly more competent and adult than yourself. Being the cat scratching at the ankles of the elephant is inherently a dangerous disorder.

      • Joshua: You weren’t referring to “excess deaths” when you made your projection.

        He was referring to deaths due to COVID-19, the counts being variously estimated. The “excess deaths” counts provide one estimate. If you disagree that the excess deaths counts is the best estimate, what estimate do you think is the best?

        Granting that measurements are estimates of quantities that can not be exactly known, and that applied mathematics is simplified approximation to complex processes, Nic Lewis’s forecasts have been among the more accurate that we have read.

      • Nic projected a number of deaths from Covid. He based in specifically on moving forward from a number listed as Covid deaths – not a number of excess deaths. He mentioned nothing about excess deaths.

        Now that it turned out that his projected number was very wrong. He wants to switch the metric that he’s using because it makes his projection look less bad.

        Excess deaths, based on a comparison to previous years, is obviously not the same thing as Covid deaths – which again, is what Nic talked about in his projection. Just as one obvious factor would be accounting for the obvious decrease in deaths from the seasonal flu that we’d see in previous years – as the result of interventions and behavior changes that targeted COVID. Of course, there could be factors that run in the other direction – such as increases in deaths in other areas because people were reluctant to seek out medical care – but in some ways those could be considered COVID deaths as well because people didn’t seek out medical care because there was a raging pandemic.

        But that’s all just bunch of related uncertainties. What isn’t uncertain is that Nic wanted to switch metrics mid-stream because he wants to make his projection look less bad than it was.

        Very disappointing.

      • > The “excess deaths” counts provide one estimate.

        You boyz are hilarious. Obviously, measuring deaths because of COVID is complicated. Many people who are in the business of counting that type of thing say that the official numbers are likely undercounts, if anything. But that’s not really here or there.

        Nic started out with a particular metric and projected forward on the basis of that metric. Now he wants to switch metrics mid-stream because he wants to diminish the appearance of having been wrong.

        Excess deaths certainly bear some kind of relationship to COVID deaths – but it’s also likely to be a very complicated relationship. What’s clear is that they aren’t the same thing. “Excess deaths” is not an estimate of COVID deaths because obviously, there are many related variables that change contemporaneously within time span that’s being considered.

        You can’t just substitute one for the other as Nic is attempting to do. If he wanted to supply some kind of translation calculus that was scientifically calibrated, and verified, then he should go ahead and do that and put it up for scrutiny.

        It’s really hilarious to watch you boyz try to dissemble for him.

        He wants to switch metrics mid-stream (without even attempting to offer a a theory of how to calibrate the one metric with the other). It’s totally unscientific. But go ahead and defend it if you want. It’s amusing and it just goes to show how “skeptics” as a group have no claim to being unbiased in their analyses.

      • There has been a sharp drop in deaths from almost all known circulating respirational diseases except from COVID-19 so teasing out meaningful information from excess death numbers will be tricky. Suicides, drug deaths, murders are up while life expectancy, family formation and child births have dropped. America is sick in many ways, sad.

      • Joe - the non epidemiologist

        Nic – I located the textbook – by Hopes Simpson. season and the epidemiology of Influenza.

        Interesting observation is that pandemics are very pronounced in the winter months for the regions north of 30degrees latitude (& south of 30S latitude). While historically between 29N to equator, there tends to be a moderately pronounced summer surge along with a somewhat moderate winter month surge.

        All of Europe is north of 35N.
        Dallas TX is 32N Houston, 29N. brownsville 26N, tallahassee 29n miami 26n.

        For the most part, the seasonal covid surges in the US and Europe are consistent with the surges documented in the 1981 era textbook.

      • “For the most part, the seasonal covid surges in the US and Europe are consistent with the surges documented in the 1981 era textbook.”

        Except… parts of the south of the US had a substantial surge during the hottest weather, which died down, and then another surge hit in the winter. Arizona had what at the time was a news-making surge in early July. It faded away, but now we have an even worse surge at the start of January. So our two surges were at the hottest time, and the coldest.

      • Joe - the non epidemiologist

        mesocycle – the moderate summer surge in AZ, TX al, ms, ga FL along with a stronger surge in the nov/Dec time frame is consistent with Hope-simpson’s analysis. 91-divoc shows AZ to have had a moderately hard surge in the summer and a harder surge in the late fall. Only difference from the Hope Simpson analysis is the AZ latitude is 32n-34n.
        I will note that CA, Oregon & WA seem to be anomalies to some extent

      • Arizona’s summer surge was hardly moderate. It almost crushed the medical system before it abated. Most of the population (and cases) was in Maricopa County, which is at moderate altitude (upper Sonoran Desert) with all the population north of 33 degrees.

        The winter surge is quite a bit worse, so far. The medical system is under significant pressure, with the largest hospital chain banning all non-emergency procedures.

        Does the textbook offer an explanation for why we get these surges? In the winter, in the Phoenix area, people are outside more than in the summer, for example.

      • Joe - the non epidemiologist

        Meso – comment – Does the textbook offer an explanation for why we get these surges? In the winter, in the Phoenix area, people are outside more than in the summer, for example.

        I havent gotten into the book enough to provide a good explanation, Though he does make reference to solar radiance/irradiance.

        I am unable to post the graph by latitude, though the image for the south of 30N shows the summer surge is approximately 2/3 of the winter surge while north of 30N has virtually zero summer surge.

        the significant deviation in the Hopes-simpson analysis is the 30n where as the deviation / dividing line seems to be approx 33n for Covid. (30S for the southern hemisphere)

      • > Does the textbook offer an explanation for why we get these surges?

        Apparently Hope-Simpson speculated about vitamin D as a moderating variable.

        https://www.hindustantimes.com/india-news/covid-19-what-you-need-to-know-today/story-rTk7VOXzuK7dCYqb3iD1IO.html

        But this armchair patten matching about lattitude is just more amusing evidence of DK as a moderating variable in the relationship between political ideology and views on COVID.

    • Mesocyclone wrote: “I suspect, but don’t know, that immunity played a significant factor [in the reduction in new cases in North Dakota since the peak around 1400/100000/day = 0.14%/day in mid-November to 250/100,000/day = 0.025%/day in mid-December], since one could reasonably project that over 50% of the population had the infection. But… a very important point that people keep ignoring… whether or not a government imposes mandates, many people will change their behavior in ways that reduce the spread of the disease. And, it is very hard to tease those changes out. You can look at mobility and guess at some of it. But the rest?”

      We’ve seen similar dramatic reductions in the Northeast this spring and the South this summer that we know haven’t been due to herd immunity for two reasons: the pandemic in these locations is surging now and cumulative detected cases there are much less than 10% (6% in FL, 6% in TX, 7.4% in AZ, 5% in NY, 5.5% in NJ). These spring and summer surges were obviously were not ended by approaching herd immunity. Limited testing capacity and changing standards for obtaining a test may have meant that undetected cases were a larger fraction of total cases (the ones resulting in immunity) were missed this spring, but probably not this summer vs this fall. Since dramatic reductions in new cases have occurred in the past because of fear and restrictions, the same factors could be at work in ND and neighboring states. I’m not sure how to personally judge the impact of changing restrictions, but I know GPS data from cells phones provides some information.

      In some locations, socio-economic factors, population density, risky jobs (meat packing plants), local politics or other unchanging factors may determine whether there are more cases in one county than a neighboring county. In those situations, one might expect to find a positive correlation between new cases and cumulative cases. However, once herd immunity becomes a major limitation in transmission to produce new cases, one might expect to find an inverse correlation between new cases and total cases. In NJ a month ago, there was a decent correlation between new and cumulative cases, R^2 = 0.6 and much weaker but not negative in ND’s counties. Unfortunately the correlation became somewhat stronger over the past month. Unfortunately, there is not much dispersion in the number of cumulative cases: 5-15% for all ND counties, 7-14% for counties over 10,000 people.

      Since I last looked, I see South Dakota is still behind ND with 11.3% cumulative cases, but three small counties have jumped to 21-22% cumulative cases. Earlier I found there was a prison in one of them (Bon Homme), so I’m not sure what to think about them. The hard hit county in Colorado in the news earlier I checked out turned out to also have a prison. (The death rate in these counties is about 50% higher than the state as a whole, but a dozen other counties exceed their death rate.) Buena Vista County in Iowa is up to 19% with the pandemic still raging (75 new cases/100,000/day. Crowley County, CO has 27% cumulative infected and I remember seeing a prison there. Bent County, 20.2% with an outrageous 314/100000 new cases/day (2%/week). There now seem to be outlier counties near 20% in many states. In general, the pandemic has moderated in the North Central US in parallel according to maps, but the cumulative cases associated with that moderation vary 2-fold. It isn’t obvious to me that herd immunity is playing a critical role in any of these reductions.

      I think a worst case scenario is that we are now missing one case for every one we detect. That would allow for some truly asymptomatic patients and some symptomatic patients not sick enough or interest in getting tested. I doubt we could be missing one case for every two or more we detect. If we were missing two cases for every one case we detect, I think herd immunity would be playing a more obvious role in places where percent cumulative cases is well into the teens and certainly at 20% – if any of those locations are “normal” and don’t have a prison. (One final possibility is that some naturally-acquired immunity fades in less than a year.). It is possible 40% or more of those younger “essential workers we intend to vaccinate before the elderly are already immune.

      • ” I doubt we could be missing one case for every two or more we detect. If we were missing two cases for every one case we detect, I think herd immunity would be playing a more obvious role in places where percent cumulative cases is well into the teens and certainly at 20% ”

        The CDC thinks we missed a higher ratio than that in the past, and I’d be surprised if we aren’t missing at least half of the cases. It was my suspicion that we are missing quite a few that led to my supposition that perhaps SD might be showing the effects of herd immunity.

        That said, we really don’t know. We have seen similar reversals of the epidemic curve in other states where we know it was not due to herd immunity, including Arizona’s summer peak – one which got world headlines at the time, but one we have now well surpassed.

        I live in AZ, and frankly do not know what is causing our current record high cases. There is certainly a lot of mobility, based on my own observations. I keep hoping for the epidemic to subside here, but so far, it has not.

        Our government has not taken strong measures, and I have the feeing that Gov. Ducey is fine to let the disease keep killing people as long as the hospitals are not overloaded – he seems to believe that he can keep the economy going without a catastrophe. Unfortunately, they are teetering on the edge of a medical system overload, which would lead to triage protocols – put another way, leaving some people to die without the care they need. Our largest hospital chain (Banner) just announced cancellation of all non-emergency procedures in their hospitals.

      • Mesocyclone wrote: “Our government has not taken strong measures, and I have the feeing that Gov. Ducey is fine to let the disease keep killing people as long as the hospitals are not overloaded – he seems to believe that he can keep the economy going without a catastrophe.”

        I’ve been saying this for many months, since May if I remember correctly. Unfortunately, we don’t have the hospital capacity to get to herd immunity in a single surge and people eventually do get scared enough – when combined with public health measures – to cause the number of new cases to fall for awhile. The 1918-20 Spanish influenza apparently occurred in three major waves in most places, probably without fully reaching herd immunity (since avian flu became a seasonal flu afterwards). Since so many middle aged people died (from cytokine storm) during the Spanish flu, fear was a much stronger motivators than during the current pandemic and the number of new cases between waves was very low.

        The people who complain about our ability to model this pandemic are probably looking at longer range predictions. If decision-makers are motivated to prevent overflowing hospitals, they need accurate projections for about eight weeks. The people getting infected today will be coming down with symptoms and testing positive about a week from now and getting sick enough to be hospitalized two weeks from now. They will stay in the hospital for an average of two? weeks. For policymakers to be able to deflect an oncoming crisis in hospital capacity, they will need to have intervened as couple of weeks ago and the wiser ones probably start a week or two earlier. The modelers probably have a better idea (but not perfect) of how much various measures will slow transmission than they did this spring, and some idea of how much role fear/voluntary measures will help, but they may want to use the latter as their safety margin and not count on it. Policymakers worried about hospital capacity probably don’t need to worry the decay of a surge or how low the number of cases will go or when they will go back up. The need a 6-8 week warning of about a coming crisis.

        My state add 50% additional ordinary and ICU beds, but they may not have the staff to fully care for patients using this surge capacity. When states talk about % of capacity, it is no longer clear what they are talking about.

  28. Nic –

    More evidence as to whether you’re in a position to weigh in on what’s “nonsense”, Nic…

    From Willis’ greatest hits:

    > So I would consider 0.085% of the population dying to be a hard upper limit on what the disease does when you do nothing. No country to date has gotten there, and there is no sign that any country will get there after the virus subsides.

    https://judithcurry.com/2020/06/21/did-lockdowns-really-save-3-million-covid-19-deaths-as-flaxman-et-al-claim/#comment-919556

    For the US, if we project from current numbers who have already died from COVID and add a projection of those that are currently infected and are likely to die…we will likely be at 0.12% at a minimum.

    Belgium is already at 0.17%

    And BTW, here’s what you said about Willis’ magical thinking…

    > the convergence in your graph of lines approaching the 0.085% of population deaths level is certainly suggestive of somewhere near that being a possible upper limit.

    https://judithcurry.com/2020/06/21/did-lockdowns-really-save-3-million-covid-19-deaths-as-flaxman-et-al-claim/#comment-919633

    I had forgotten that you speculated about Sweden topping out at 0.06%. They’re at 0.086% already. Looking at infections and ICU admission there now, (let’s conservatively say a minimum of 50 deaths per day for another month) and they’ll be at 0.1% before “peter[ING] out.” In fact, it’s not too unlikely that multiplying your speculated number by 200% will be much closer to the final number than what you anticipated.

    You might be better off if you paid more respect to Mr. Uncertainty.

    • Oh. Forgot to mention, we’re already at more than 25 countries that have surpassed the population fatality rate that you and Willis speculated would be a “hard limit.” “No sign any county would get there” my a$$.

      How many will get there eventually, and even more to the point how many more would have gotten there absent vaccines despite your erroneous calculations about the effects of “herd immunity?”

      • Joshua: we’re already at more than 25 countries that have surpassed the population fatality rate that you and Willis speculated would be a “hard limit.”

        Nobody has written “admirably” accurate prognostications. Willis Eschenbach’s on that date have been more accurate than most (than any?)

        Deaths today in the US stand at 0.1% of the population at risk, much higher in some states than others.

        did-lockdowns-really-save-3-million-covid-19-deaths-as-flaxman-et-al-claim?

        No. Willis Eschenbach’s calculations are conclusive on that point.

        You might be better off if you paid more respect to Mr. Uncertainty.

        Confidence limits on the “hard limit” might have been a worthy addition to Willis Eschenbach’s essay, had we thought to calculate estimates of them. I had some thought about the uncertainty of estimating an upper bound, but I don’t think I wrote it, so I can’t take credit.

      • The errors that other people made in no way makes Willis’ overconfidence pronouncements, based on magical thinking, and Nic’s co-signing onto those overconfident pronouncements, any wrong.

        > Confidence limits on the “hard limit” might have been a worthy addition to Willis Eschenbach’s essay, had we thought to calculate estimates of them.

        See, that’s the problem. Some people make magical-thinking, over-confident statements based on looking at lines on a graph.

        Other people do fundamental study and take the time to publish their work along with estimates of uncertainty. Of course those estimates of uncertainty could be wrong, but I think that formally estimating uncertainties is a better way to go.

      • …any less wrong.

    • Joshua, quoting Nic Lewis: > the convergence in your graph of lines approaching the 0.085% of population deaths level is certainly suggestive of somewhere near that being a possible upper limit.

      “Suggestive of somewhere near that” is certainly suggestive of uncertainty. Looking across the range of errors encountered by other forecasters, it is hard to deny that 0.2% is “somewhere near” 0.085%. But as I wrote elsewhere, it would have been better had we thought to compute a confidence interval for the upper limit.

      Meanwhile, San Diego County, CA has taken a turn for the worst since or coinciding with the most recent “lockdown”.
      https://www.sandiegouniontribune.com/tracking-coronavirus-cases-san-diego-county

      Follow links to other graphs to see the dramatic increase since about mid-Nov. Latest lockdown order was Dec 7, and if it made a difference that difference is not discernable in the graphs (or anywhere else in CA that I have seen so far.)

      • > it is hard to deny that 0.2% is “somewhere near” 0.085%.

        In absolute terms, sure. In relative terms, based on where the numbers were when he made that projection, not so much. For example, IIRC, the number in Belgium was close to 0.85 at the time. I could dig back through and check because I commented on it at the time, but lets say it was as low as 0.07% at the time (it wasn’t, but we’ll go for that for the sake of argument).

        So Willis projected a growth of, say, 0.015% before the pandemic dies when actually in Belgium it grew by close to 0.1% or something like that. That’s quite substantial. And Nic signed on. The estimation may even be off by an order of magnitude by the time all is said and done.

        So that’s the most extreme example among countries of significant size. But by the time is over they will be off by a very significant % in a slew of countries. Perhaps 1/2 an order of magnitude in many.

      • While obviously still very high, there may be some hope of preliminary signs that the growth in case rate in Cali may be leveling out. Illness and deaths will still increase for weeks (because you can’t decouple positive tests from increased in hospitalizations, ICU admissions, and deaths) but maybe, hopefully flatten after that point.

        Unfortunately, there don’t seem to be signs of the same flattening out in the other largest states, New York, Florida, and Texas. Let’s hope that changes.

    • Re: “the convergence in your graph of lines approaching the 0.085% of population deaths level is certainly suggestive of somewhere near that being a possible upper limit.”

      Ludicrous. The population fatality rate (PFR) is an order of magnitude larger than that in a number of places, often going above 0.5%. This is another great example of why most climate “skeptics” should just be ignored on COVID-19. Their political ideology blinds them to reality, both on medical science and climate science.

      “The municipality of Castiglione d’Adda, a rural town of about 4550 inhabitants located South-East of Milan, has been heavily affected by SARS-CoV-2 infection […]. At the same time, 47 deaths were officially attributed to COVID-19.”

      Click to access 2020.06.24.20138875v2.full.pdf

      “During a four-month period, 1.6% of the entire adult population of Atahualpa, including 6.9% (27/392) of older adults, died from SARS-Cov-2-related causes.”
      https://www.sciencedirect.com/science/article/pii/S1201971220306305#bib0030

      [with: https://coronavirus.jhu.edu/us-map%5D

  29. My full respect to the UK health staff and frontline workers but the latest news is hinting at full lockdown until the end of the year, when vaccinations have finished being rolled out.

    A whole nother year (?)

  30. Interesting take from a credible source regarding more 1-shot vaccinations versus fewer 2-shot vaccinations.

    • It seems anywhere from 20-40% of health workers have refused to take the vaccine (or opted not to take it, if that sounds better).

      Is that a glitch in the matrix, Joshua?

    • Cheby –

      There are many potential glitches. Perhaps the efficacy of vaccines will be eliminated in different virus variants. We may only be at the top of the 3rd or bottom of the 4th inning.

      But I wouldn’t be surprised that if the vaccines show benefit, people will get vaccinated at increasing rates. No reason to believe that %’s not getting it now will stay constant.

  31. Some good news for the UK:

    “Despite apocalyptic visions of traffic chaos at British ports, HGVs flowed freely to and from Dover and the Channel Tunnel today as the new UK-EU trading relationship was put to the test.”

    https://www.thetimes.co.uk/article/lorry-load-of-strawberries-is-first-casualty-of-brexit-xtq7dv59j

    • I’ve read that many hauliers are holding back, waiting to see how others cope with things, and lots of stockpiles were built up before the deadline so we’ll know more over the next week or two.

      Scotland hope to return to Europe soon!

  32. More confirmation that it’s health staff burn-out, working 11hrs/wk more and scared of catching covid themselves. It’s a terrible burden that has been placed upon them:

  33. B.1.1.7 – the important part is that this is the final number the herd will remember from OPERATION COVIDIUS, since this one is clearly running out of gasoline!

  34. Richard Greene

    Previous articles by Nic Lewis on COVID herd immunity were speculation, and it now appears his herd immunity beliefs were wrong. I wrote at the time it was too soon for his articles — in the middle of the pandemic.

    So I was not a fan when I started reading … but this article is well written, well documented, presents evidence clearly, and does not seem to jump to any conclusions.

    The final sentence may be the most important sentence in the article:
    “It is highly desirable that no SARS-CoV-2 or COVID-19 related report or study should hereafter be considered by the government or its advisers unless it is accompanied by a link at which all the data used is available.”

    • Joe - the non epidemiologist

      Regarding Nic’s early assessment of Herd Immunity / HI threshold, In 2-3 years, Most of what we believe is true at this point in time will be found to be wrong.

      One good thing in Nic’s assessment is that it is not governed by “Covid-freakout science.

      Lets wait until things shake out, and we can make a rational assessment before we claim someone was “Wrong”

    • Richard Greene: So I was not a fan when I started reading … but this article is well written, well documented, presents evidence clearly, and does not seem to jump to any conclusions.

      I agree. I earlier questioned whether “herd immunity threshold” had any practical meaning. I found this essay better than the earlier ones.

    • Although I was initially skeptical that heterogeneity could reduce the HIT, I was surprise to have read about this possibility at Climate Etc a month or two before it was in the news section of Science and Nature. That’s pretty impressive company. And when I had enough time to digest the idea, it became clear to me that “gregarious people” are more likely to become immune earlier in a pandemic than “hermits”. In this sense, heterogeneity certainly exists and lowers the HIT. Unfortunately, no one knows how much it lowers the HIT. The problem with a heterogeneity parameter is that no one knows how big is should be. A large heterogeneity parameter illustrates the POTENTIAL importance of the phenomena. Other misleading information from early seropositivity studies and from Sweden added to the confusion. At the end of spring, several groups and the CDC wrongly concluded that there were between 6 and 15 missed cases of COVID for every one detected by PCR. That lead to a serious under-estimate of the IFR and the absurd idea COVID was no more deadly than influenza. It also suggested we could be much closer to herd immunity than Today, with 12.2% of the population of North Dakota having tested positive, we know that the number of undetected infections must be much lower, perhaps 1-2 undetected cases for every one we detect.

      After Nic’s first posts, I had been looking for any location where there have been two major surges. Surges in many Southern states occurred this summer, but not where they occurred in spring. Louisiana had a spring and summer surge, but they were in different counties. Was herd immunity preventing a second surge? Or was fear from an earlier surge causing people to be more cautious? It wasn’t until cases surged for a second time in France in late August, that it became clear that their first surge wasn’t ended by approaching herd immunity – unless the surges occurred in different regions of France. The first fall surges in the US were also in a new location, the north central states, and cumulative cases shot past all earlier records. In the past two months, it has finally become clear to me that surges are occurring in places that were hit hard this spring and summer.

      • Frasnk

        That is an interesting comment

        “And when I had enough time to digest the idea, it became clear to me that “gregarious people” are more likely to become immune earlier in a pandemic than “hermits”

        Our Northern cities in the UK were hit very hard by infections and I put that down to the far more gregarious nature of Northerners-especially the young-compared to Southerners. They like to mix and socialise far more than many of us in the south.

        tonyb

      • Frank –

        > The problem with a heterogeneity parameter is that no one knows how big is should be. A large heterogeneity parameter illustrates the POTENTIAL importance of the phenomena. Other misleading information from early seropositivity studies and from Sweden added to the confusion. At the end of spring, several groups and the CDC wrongly concluded that there were between 6 and 15 missed cases of COVID for every one detected by PCR.

        Keep in mind that the case ascertainment rate has undoubtedly been increasing over time. I’m sure we’re capturing a higher % of true cases than we were in the beginning months when there was such a shortage of available testing and many times only the infectious (or even seriously ill) were being tested.

        So…

        > perhaps 1-2 undetected cases for every one we detect.

        We have to account for the long stretch when it was higher than it was when infections started spiking in the Dakotas

        Of course, in a theoretical sense, with the very first infection in the US, the pool of people to potentially get infected was reduced. In the vague way that proponents of this theory use the term, “herd immunity” had begun. But at what point guess the number of infected truly cause the rate is spread to be significantly, differentially slowed down? As opposed to the effect of NPIs? Or behavioral changes out of fear? Or wearing masks?

        It’s remarkable that to me that people like Nic are so confident they can accurately calculate that.

        We’ve hit 20 million tested positive in the US What factor do you want to use to calculate actual # of infections? 40%? 2X? 5X? 10X?

        Let’s say it’s 4X. 80 million people. Close to 25% of the population. It’s a staggering number.

        Do we see signs of slowing down? So you might answer “CASEDEMIC!.”. But the problem with that is that we are recording record numbers of deaths or at least relatively very high numbers of deaths day after day and it’s still rising. It will probably rise or stay high for another month at least.

        > perhaps 1-2 undetected cases for every one we detect

        Keep in mind, if it were 4 X undetected cases for every detected case (cumulatively), that’s 80 million people and that would mean the IFR is…. well, I’m not good at math, so I’ll let David Young figure that out. I mean it must be Ioannidis’ calculation of 0.03% is correct as David insists, right?

      • I have wondered if ND might have come close to HIT in its surge. It had enough cumulative cases per capita that with a not crazy guess at missed cases, it could have been close enough that at immunity might have been a significant, if not the only factor in its downturn. Or, it might not have – I am just wondering, not asserting.

        The impact of immunity grows linearly with immunity. All else held equal Rt = R0*(susceptible / total population).

      • Sorry. Meant to say 0.3% for Ioannidis’ IFR and just 1 undetected case for every detected case, or 40 million.

        Anyway, geeze, I hope David comes round to calculate that for us. I suspect that the number of cases detected won’t just stop tomorrow, and I can’t calculate it myself but I think that at 40+ million cases, Ioannidis’ IFR calculation might turn out a tad low, but David kept insisting it was spot on!

      • ” I had been looking for any location where there have been two major surges. ”

        Frank, I’ve been posting here about Arizona’s two surges – did you miss that.

        Our summer surge was so dramatic that it made headlines around the world. We are now in our winter surge and it is much higher. Check out 91-divoc for the curves. Our hospitals are in just as bad a shape as they were during the summer surge – so far.

        Oh, and the state just reported positive case counts for two days with significantly higher counts than any in our past – at 11,000+ cases each (the previous record was about 8500).

      • I was going to suggest that in Arizona, maybe while the # of cases spiked higher than earlier, maybe the deaths hadn’t.

        Then I looked. Not good

      • “I was going to suggest that in Arizona, maybe while the # of cases spiked higher than earlier, maybe the deaths hadn’t.

        Then I looked. Not good”

        Exactly. 91-divoc lets you plot deaths and cases on the same graph (different scales optional). It’s easy to see how well they do or don’t track.

        I would not be surprised if Arizona will face harsher control measures next week. Meanwhile, it is hazardous to get medical care, and my family members have some that cannot wait.

      • I wish your family well.

        With care, probabilities are still in an individual’s favor, but it’s not getting better and the longer this stretches out, the more even good odds effectively dissipate.

      • Mesocyclone and Josh: Thanks for pointing out Arizona to me, Meso. I’ve been focused on the Dakotas and surrounding territory, where the fall surge struck first and new cases are now way down. ND: 31 current cases per 100,000/day (about 20% of peak in mid-November). 12.2% cumulative detected infections – almost all in the fall when we can hope that the ratio of total cases to new cases was stable. There is no conclusive way to tell if this slowdown represents approaching herd immunity.

        AZ adds some new information. State-wide cumulative case are 7.9% of population (well below ND) and current surge hasn’t quite matched ND’s peak. However, the worst of the summer surge was localized in Yuma and Santa Cruz counties, where cumulative cases now total 13.6% of the population. AND where the pandemic clearly hasn’t subsided due to approaching herd immunity: 140 & 150 new cases per 100,000/day. This is the highest number of new cases/day I’ve seen combined with the highest number of cumulative cases – ie the best evidence that approaching herd immunity isn’t having an important impact when 13% of the population is known to be immune. That would be 26% or 39% immune if testing missed only one or two asymptomatic or mildly symptomatic cases for every case detected (reasonable lower and upper limits). And if detection was less efficient this summer, 13% cumulative cases in both ND and Yuma would represent somewhat higher estimated total immunity in Yuma (unless immunity weakens over six months).

        Rightly or wrongly, Nic has suggested that deaths are more reliable measure of the pandemic than detected cases (though deaths involve small numbers and associated noise in some places). If so, total deaths per 100,000 in ND (175) have effectively caught up with the long time leaders NJ/NY/MA from the spring surge (about 200). Cumulative detected cases amount to only 5-6% of population in these three state. If deaths were the true measure of total infections, then we missed about twice as many cases in NY/NJ/MA per detected case this spring as we did in ND this fall. Of course, there are two big problems comparing cases with deaths: improving treatment and falling age of the average person infected. Both suggest that missing twice as many cases earlier in the pandemic is likely somewhat too high.

        The good news is that surges so far have only lasted only a month or two. I predict that AZ will be under 40-50 new cases/day/100,000 by February 1. Belgium is the most extreme example reaching 160 new cases/day per 100,000 two months ago, but remaining above 80 for only 20 days and above 40 for only 37 days. It seems to me that surges are always suppressed by public health measures implemented for fear of overflowing hospitals or by people’s fear when they recognize there may not be a hospital bed available if they get sick. And the more severe the surge, the shorter it seems to last. Every US state has take different paths at different times, but cumulative cases amount to 8+/-4% across all but a few states.

      • “The good news is that surges so far have only lasted only a month or two. I predict that AZ will be under 40-50 new cases/day/100,000 by February 1. ”

        Thanks for your analysis re: herd immunity.

        As an Arizona resident, I sure hope you’re right that the surge will drop. I am not seeing many signs that people are becoming less careless. And, some schools are still open. Meanwhile, we just have to hope that we don’t need medical care – but… a person close to me needs surgery that cannot wait until February.

        Sooner or later something will have to give. The Catholic Diocese of Tucson, for example, just banned almost all in-person masses. If their past policies have matched that of the Phoenix Diocese, then they were already taking pretty good precautions – 25% capacity at mass, mandatory masks, etc.

        I think that Santa Cruz and Yuma counties aren’t very good places to draw conclusions from, because they have so many cases being imported from across the border, plus they have a low population.

    • mesocyclone: “The impact of immunity grows linearly with immunity. All else held equal Rt = R0*(susceptible / total population).”

      That is only true in the case of a homogeneous population. Where there is heterogeneity in susceptibility then the immunity factor lambda (which depends also on how strongly variability in susceptibility is correlated with variability in infectivity, via people’s social connectivity) comes in. The relationship then is:
      Rt = R0 * (susceptible / total population)^lambda.
      See Tkachenko et al. Eq.[15]. They estimate that lambda = ~4.
      https://doi.org/10.1101/2020.07.26.20162420

  35. Robert Clark

    date isolated increase % total tests
    12/16/2020 213,811 39,522 22.7 1,789,897
    12/17/2020 191,082 22,729 -10.6 1,730,046
    12/18/2020 208,870 17,788 9.3 2,218,532
    12/19/2020 172,190 -36,680 -17.6 1,959,160
    12/20/2020 175,328 3,138 1.8 1,784,786
    12/21/2020 174,073 -1,255 -0.7 2,115,141
    12/22/2020 155,015 -19,058 -10.9 1,600,123
    12/23/2020 203,467 48,452 31.2 2,148,367
    12/24/2020 171,423 -32,044 15.7 1,724,348
    12/25/2020 97,800 -73,623 -42.9 1,365,808
    12/26/2020 136,245 38,445 39.3 2,009,675
    12/27/2020 121,090 -15,155 -11.1 1,463,298
    12/28/2020 159,062 37,972 31.4 2,208,669
    12/29/2020 167,976 8,914 5.6 1,753,827
    12/30/2020 209,077 39,101 23.2 877,253
    12/31/2020 200,155 8,922 4.3 1,881,920
    1/1/2021 160,801 -39,354 -19.6 1,320,033
    1/2/2021 202,652 41,852 26 1,818,100
    202,652 is 11.1% of total tests.
    Had to move. Stayed to long there.
    Things should be back to normal by Tuesday. The holidays are over.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      187,038 is 12.1% of total tests.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      154,807 is 9.3% of total tests.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      215,456 is 10.6% of total tests.
      Hopefully all are back to work. They have all the numbers up to date. We will see where things go from here.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      231,800 is 14.7% of total tests.
      Today was not for the Republic’s best.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      220,634 is 12% of total tests.
      All should be back to work and numbers caught up.
      Tomorrow is another day.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      262,892 is 12.9% of total tests.
      It appears they may still be updating.
      Tomorriw is another day.

    • Robert Clark

      date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      218,997 is 10.2% of total tests.

    • date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      264,265 is 10.3% of total tests.

    • date isolated increase % total tests
      12/26/2020 136,245 38,445 39.3 2,009,675
      12/27/2020 121,090 -15,155 -11.1 1,463,298
      12/28/2020 159,062 37,972 31.4 2,208,669
      12/29/2020 167,976 8,914 5.6 1,753,827
      12/30/2020 209,077 39,101 23.2 877,253
      12/31/2020 200,155 8,922 4.3 1,881,920
      1/1/2021 160,801 -39,354 -19.6 1,320,033
      1/2/2021 202,652 41,852 26 1,818,100
      1/3/2021 187,038 -15,614 -7.7 1,541,675
      1/4/2021 154,807 -32,231 -17.2 1,664,910
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/11/2021 196,971 9,919 5.3 2,101,922
      196,971 is 9.4% of total tests.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      208,180 is 11.3% of total tests.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      193,849 is 9.6% of total tests.
      Back in June you brought the daily positives down to 20,000. We figured out that it remained there because that was what the virus made in the first 4 days before the test could detect it. I believe we are at that point again. The asymptomatic are making an average of 2,000,000 positive daily. It will probably stay here until the vaccine begins lowering the asymptomatic.. Hopefully it has begun.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      215,727 is 9.3% of total tests.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      194,581 is 7.3% of total tests.
      Total % down 22.5%. Total tests up 14.8% Those numbers do not make sense.
      Tomorrow is another day.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      166,468 is 8.3% of total tests.
      The new President has not taken the oath yet.
      Tomorrow is another day.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 _-36,678 -22 2,095,254
      129,790 is 6.2% of total tests.
      If there are any of you reading this (which I doubt) you are finally seeing the results of your work. Your job was to find the infected. The contact tracers tracers used your findings and above is the results.
      THANK YOU!!!
      Just for me ,if you are there, a 3 word reply.
      YOU ARE WELCOME

      • How about explaining what this is. I got a bunch of emails of your comments, witnb no idea what these columns mean.

      • This is me following the virus. I started in March and we just Began lowering the daily growth.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      142,492 is 8.2% of total tests.

      • date isolated increase % total tests
        2/11/2021 94,195 6,460 7.3 1,592,480
        2/12/2021 91,083 -3,112 -3.3 1,833,118
        2/13/2021 78,271 -12,812 -14 1,723,298
        2/14/2021 63,446 -14,825 -18.9 1,745,616
        2/15/2021 49,567 -13,879 -21.9 1,253,530
        2/16/2021 57,024 7,457 15 1,085,182
        2/17/2021 67,132 10,108 17.7 1,236,497
        2/18/2021 61,480 -5,652 -8.4 2,685,892
        2/19/2021 71,335 9,855 16 2,010,675
        2/20/2021 62,426 -8,904 -12.4 1,009,330
        2/21/2021 51,106 -11,320 -18.1 3,619,308
        2/22/2021 50,911 -195 -0.4 1,295,489
        2/23/2021 65,651 14,740 29 1,520,891
        2/24/2021 64,969 -682 1 1,457,049
        2/25/2021 73,827 8,858 13.6 1,766,243
        73,827 is 4.2% of total tests.
        1,766,243 total tests. Maybe you are sill out there. 2,000,000 is just 233,757 tests more.
        Have you noticed that they are talking about the drop in hospitalization and deaths over the last few weeks? THAT IS ALL DUE TO THE WORK OF THE CONTACT TRACERS AND TESTERS.
        Tomorrow is another day.

    • date isolated increase % total tests
      1/5/2021 215,456 60,649 39.2 2,039,242
      1/6/2021 231,800 16,314 7.6 1,574,773
      1/7/2021 220,634 -11,166 -4.8 1,838,358
      1/8/2021 262,892 42,258 19.2 2,037,061
      1/9/2021 218,997 -43,895 -16.7 2,154,033
      1/10/2021 264,265 45,268 20.7 1,981,459
      1/11/2021 187,052 -77,213 -29.2 1,925,416
      1/12/2021 196,971 9,919 5.3 2,101,922
      1/13/2021 208,180 11,209 5.7 1,837,552
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      173,864 is 9.0% of total tests.
      I asked if any of you were left and heard nothing. .Then I saw the above. To mesocyclone I apologize and say thanks. Not only are some left, but someone wants to stop. I was thinking about it. Not anymore.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 -0.1 1,941,481
      173,615 is 8.9% of total tests
      Tomorrow is another day.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      179,455 is 9.4% of total tests.
      The contact tracers, testers and antibodies have been keeping the daily positive relatively constant. That means that about 14 days from today they will have given a 3 month+ vaccine to 358,910 as a result of today’s work. They have been doing that daily. That is the result of your findings in the first six months.
      THAT IS WHAT YOU HAVE DONE. ONLY THE VACCINE DESIGNERS AND PRESIDENT TRUMP CAN MATCH THAT!!!!!

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      164,328 is 7.6% of total.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      120,927 is 7.5% of total tests.
      Understand that the first to be vaccinated were essential (those most likely to be unknowing) workers.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      133,462 is 7.1% of total tests.
      It was treading water for quite a long time. Could something have changed to begin bringing down the percentage?

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      135,036 is 7.4% of total tests.They are still keeping the test numbers high while vaccinating many.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      127,870 is 8.4% of total tests

      • This is not the place for this so apologize to you all!
        You watch the wounded warrior commercial and then you think about what our government has done over the last 2 weeks.
        WHAT HAVE WE, THE AMERICAN PEOPLE, LET HAPPEN????

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      145,331 is 7.2% of total tests.
      I apologize again for the above. Back to non political.

      • Why do you keep posting long lists of unlabeled statistics? Asking again.

        If they are unavailable elsewhere, how about a standard heading to those posts so we know what you are posting about.

      • yes I’m waiting for the answer to this one

      • A short explanation:
        14 days ago The testers asked 166,468 ASYMPTOMATIC TO SELF ISOLATE. Today they asked 145,310 to do the same. The total tests today was 2,025,380. The only number that means anything is 7.2%. That is the % of those that was asked to self Isolate.
        Today 166,466 individuals theoretically were cured and vaccinated for 3 plus months. Because of the vaccine we are not treading water anymore. That means that more than 145,310 Asymptomatic were unknowingly cured today and self vaccinated.
        To put it bluntly the % should be going straight down

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      153,742 is 7.7% of total tests. The contact tracers and testers are keeping the number high. Those injecting the vaccine are doing better each day. All is looking well.

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      124,288 is 5.9% of total tests.
      No 4 letter word yet. I will wait a couple of days.
      To the contact tracers and testers.. It takes 18 days to go from infected to cured by antibodies. Keep the total daily tests close to 2,000,000 for the next 36 days. Then we will see where we are.
      To the Government. Finish the wall and stop the caravans. The AMERICAN PEOPLE fought hard to get us here. DO NOT SCREW IT UP!!!!

    • date isolated increase % total tests
      1/14/2021 193,849 -14,331 6.9 2,015,420
      1/15/2021 215,727 21,878 11.3 2,329,042
      1/16/2021 194,581 -21,146 -9.8 2,674,952
      1/17/2021 166,468 -28,113 -14.4 1,990,040
      1/18/2021 129,790 -36,678 -22 2,095,254
      1/19/2021 142,492 12,702 9.8 1,736,553
      1/20/2021 173,864 31,372 22 1,921,529
      1/21/2021 173,615 -249 0.1 1,941,481
      1/22/2021 179,455 5,840 3.4 1,914,077
      1/23/2021 164,328 -15,127 -8.4 2,152,320
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      103,155 is 6.2 % of total tests.
      Tomorrow is another day.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      11o,133 is 5.8% of total tests.
      Tomorrow is another day.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      108,030 is 6.4% of total tests.
      % up from yesterday with the total tests down. Not a good sign.
      Tomorrow is another day

      • Since 12/3/2020 thru 2/2/2021 the contact tracers and testers have found 10,946,647 infected individuals and asked them to self isolate in the United States.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      102,535 is 7.1% of total tests,
      The only explanation I can think of is the drive-in tests are going down, thus the % of contact tracers is going up.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      110,363 is 6.9% of total tests.
      Looks like we are still treading water.
      The vaccine should kick in soon. They did the essential workers first. Now us old folks that are hiding from the virus waiting for the vaccine.
      Tomorrow is another day.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      111,681 is 6.3% of total tests.
      For those that may still be with me, remember April and May. We are back there. Now we have the testers and contact tracers with the knowledge to go well past 20,000 daily positive.
      MORE TESTS!!!!! I REPEAT. MORE TESTS11111

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 9,357 8.3 1,723,989
      102,324 is 5.9% of total tests.
      Still treading water. More tests!

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 9,357 8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      86,592 is 5.0% of total tests.

      !!!!!!!!!! WOWW !!!!!!!!!!

      Back in March of 2020, somebody did something.
      He stopped all elective surgery.
      About a month later, somebody did something.
      He asked you give your employees a $50.00 gift card if they got a COVID test.
      Today the AMERICAN PEOPLE showed that they are the best.
      After 1/20/2021 somebody did something. Now the building of the wall has stopped and the borders are open.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      80,375 is 5.5% of total tests. We do not to tread water.
      The CDC is to give a recommendation about schools Wednesday.
      They, of all organizations, should know what the contact tracers and testers have done. We will see.
      MORE TESTS. We do not to tread water. Keep ahead of the antibodies.

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      86,542 is 5.0% of total tests.
      279,677 more tests and only went down .5%.
      MORE TESTS

    • date isolated increase % total tests
      1/24/2021 120,927 -43,401 -26.4 1,614,982
      1/25/2021 133,462 12,535 10.4 1,881,342
      1/26/2021 135,036 1,574 1.2 1,820,592
      1/27/2021 127,870 -7,166 -5.3 1,519,170
      1/28/2021 145,310 17,440 13.6 2,025,380
      1/29/2021 153,742 8,432 5.8 2,001,004
      1/30/2021 124,288 -29,454 -19.1 2,095,254
      1/31/2021 103,155 -21,133 -17 1,676,717
      2/1/2021 110,133 6,978 6.8 1,888,276
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      87,735 is 5.7% of total tests.
      More tests. You can not let the virus make more positives daily than the contact tracers and testers ask to self quarantine daily.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      94,195 is 6.1% of total tests. Treading water means we are asking 90,000 positive daily to self isolate and antibodies are curing 90,000 infected daily while the asymptomatic are infecting the 180,000 daily. 3,000+ illegals’ coming over the southern border daily. They definitely have an infection rate over 6.1%.
      MORE TESTS!!!!!

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      91,083 is 5.0% of total tests.. 2,000,000 tests would be better. Remember there is a 5 day delay for the positive drop to show.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 14 1,723,298
      78,271 is 4.5% of total tests.
      We nee 2,000,000 tests a day to stay ahead of the antibodies.
      -14% above.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 18.9 1,745,616
      63,446 is 3.6% of total tests.
      DONALD J. TRUMP HAS SUCCEEDED, WITH HELP OF THE AMERICAN PEOPLE. CONTACT TRACERS, TESTERS, AND PUBLIC-PRIVATE PARTNERSHIPS, IN DEFEATING THE VIRUS.
      The above shows that the VACCINES are the last part of the solution. The vaccines are meeting the virus at day one of the potential infection. Days 1 thru 4 are now being eliminated.
      KEEP THE SOUTHERN BOARDER CLOSED AND OPEN UP THE COUNTRY.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      49,567 is 4.0% of total tests.
      !!!!! WOWW !!!!!

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      57024 is 5.3% of total tests.
      Not what I expected.
      Tomorrow is another day.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      67,132 is 5.4% of total tests.
      3 days ago it was 3.6%.
      In September the contact tracers began the wait 6 days and then test those in contact with the positive. They have worked very hard to get it to the 3.6% number.
      What has changed recently? Ask Governor Cuomo if he has any idea?

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      61,480 is 2.3% of total tests.
      The actual % for today is around 5.5% because they added over 1,500,000 tests to the total tests after 24:00GMT.
      Tomorrow is another day. I do believe by opening the border puts us back to June when you had it near 20,000 positive per day. You saw how hat turned out until the contact tracers began the 6 day rule.

      • All they talk about is Cuomo while Biden opened the border and we are loosing it. HOW MANY WILL DIE NOW. THE VACCINE CAN NOT STOP THIS.

    • date isolated increase % total tests
      2/2/2021 108,030 -2,103 -1.9 1,676,233
      2/3/2021 102,535 -5,495 -5.1 1,435,913
      2/4/2021 110,363 6,828 7.6 1,589,753
      2/5/2021 111,681 1,318 1.2 1,780,108
      2/6/2021 102,324 -9,357 -8.3 1,723,989
      2/7/2021 86,592 -15,732 -15.3 1,443,646
      2/8/2021 80,375 -6,207 -7.2 1,457,166
      2/9/2021 86,542 6,167 6.8 1,736,843
      2/10/2021 87,735 1,193 5.7 1,529,031
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      71,335 is 3.5% of total tests.
      Similar to yesterday they raised the total tests twice during the afternoon.
      As you can see by the total positive we have lost control of the virus.
      I HAVE ANOTHER STUPID IDEA. It worked once maybe it will work again. Of coarse this time we need millions.
      Copy and paste his total post and send it to each of your Senators and your Representative in the House. GET AS MANY OF YOUR FRIENDS AND RELATIVES TO DO THE SAME.
      CLOSE THE BORDER!!!!! CLOSE THE BORDER!!!!!

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 8,909 12.4 1,009,330
      62,426 is 6.2% of total tests.
      Have not heard anything about closing the border. Probably after they pass the $1.9 trillion Bill they will let us clean up the virus again. By then it will probably take another 3 months.

      • Today, on the CDC that changes at 1200 GMT, they are showing it will be over 96,000 total positive and over 3.5 million tests. They can not fudge the positives.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      51,106 is 1.4% of total tests.
      If you believe today’s readings from the CDC there is a bridge for sale in Brooklynn.
      Tomorrow is another day.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      2/22/2021 50,911 -195 -0.4 1,295,489
      50,911 is 3.9 of total tests.
      Contact tracers and testers are keeping it treading water. We will see in the next week or so if they. can keep it there.
      I did not hear anything about Congress seeing a grass routs demand to shut the border back down. Wishful thinking on my part.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      2/22/2021 50,911 -195 -0.4 1,295,489
      2/23/2021 65,651 14,740 29 1,520,891
      65,651 is 4.3% of total tests.
      As far as the virus goes, those crossing the boarder illegally with the caravans may have a lower infection percentage rate than I thought. From infection to cure takes about 18 days. A very high percentage may have been asymptomatic while the symptomatic stopped or died.
      The number of infected is ONLY 500,000 individuals because of the work the AMERICAN PEOPLE, contact tracers, and testers did.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      2/22/2021 50,911 -195 -0.4 1,295,489
      2/23/2021 65,651 14,740 29 1,520,891
      2/24/2021 64,969 -682 1 1,457,049
      64,969 is 4.7% of total tests.
      It appears to me , if we want the country open we have to get the total tests back up to 2,000,000 tests a day.. The vaccine reaction is to slow and you have shown if you get it up to 2,000,000 tests a day the results are the next day.

      • The above, I meant the number of deaths from COVID-19 is ONLY 500,000 because of the work done to get asymptomatic to self isolate by the AMERICAN PEOPLE, CONTACT TRACERS AND TESTERS. i BELIEVE BACK IN MARCH AND APRIL THE ESTIMATE WAS IN THE MILLIONS.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      2/22/2021 50,911 -195 -0.4 1,295,489
      2/23/2021 65,651 14,740 29 1,520,891
      2/24/2021 64,969 -682 1 1,457,049
      2/25/2021 73,827 8,858 13.6 1,766,243
      73,827 is 4.2% of total tests.
      1,766,243 total tests. Maybe you are sill out there. 2,000,000 is just 233,757 tests more.
      Have you noticed that they are talking about the drop in hospitalization and deaths over the last few weeks? THAT IS ALL DUE TO THE WORK OF THE CONTACT TRACERS AND TESTERS.
      Tomorrow is another day.

    • date isolated increase % total tests
      2/11/2021 94,195 6,460 7.3 1,592,480
      2/12/2021 91,083 -3,112 -3.3 1,833,118
      2/13/2021 78,271 -12,812 -14 1,723,298
      2/14/2021 63,446 -14,825 -18.9 1,745,616
      2/15/2021 49,567 -13,879 -21.9 1,253,530
      2/16/2021 57,024 7,457 15 1,085,182
      2/17/2021 67,132 10,108 17.7 1,236,497
      2/18/2021 61,480 -5,652 -8.4 2,685,892
      2/19/2021 71,335 9,855 16 2,010,675
      2/20/2021 62,426 -8,904 -12.4 1,009,330
      2/21/2021 51,106 -11,320 -18.1 3,619,308
      2/22/2021 50,911 -195 -0.4 1,295,489
      2/23/2021 65,651 14,740 29 1,520,891
      2/24/2021 64,969 -682 1 1,457,049
      2/25/2021 73,827 8,858 13.6 1,766,243
      2/26/2021 70,940 -2,887 -3.9 1,803,122
      70,940 is 3.9% of total tests.
      200,000 tests short of 2,000,000 tests, but positive % of total tests is gradually going down.
      Tomorrow is another day.

  36. nickreality65

    Between 12/9/20 and 12/23/20 CDC logged 30,227 deaths attributed to C-19. There were 148,206 deaths due to all causes. The 65+ demographic was accountable for 85% of those C-19 deaths.
    85.6% of C-19 CASES are among those UNDER 65 years of age. (CDC)
    80.7% of C-19 DEATHS are among those OVER 65 years of age. (16% of population)
    24.8% of C-19 deaths occurred in nursing homes and hospice care.
    Over half of the CASES never see a doctor, hospital or morgue.

    If you are 65+ w multiple health issues in a crowded nursing home and the staff brings in C-19 you are screwed, but then you were screwed anyway.
    In other words: If you are already seriously ill, C-19 will probably finish you off, i.e. no different from the seasonal flu or pneumonia

    C-19 is not a problem for the young and healthy herd. Mother Nature and her buddy Grim Reaper are just doing their jobs, culling the herd of the too many, too old, too sick warehoused too close together as Medicare/Medicaid cash cows in poorly run contagious lethal elder care facilities.

    Japan has the highest percentage of 65+, 27%, yet still under 4,000 deaths. (WHO)
    What do they know/do the rest of the world does not?

    If C-19 is mostly killing off old sick people why are our elected morons suspending civil liberties, due process, bankrupting the country with lockdowns, distancing and masked clown shows?
    Guess they can’t impose the NWO Grand Reset with actual facts.
    And the lying, fact free, fake news MSM left-wing propaganda coup machine has betrayed its responsibility to democracy and an informed public.

    • “In other words: If you are already seriously ill, C-19 will probably finish you off, i.e. no different from the seasonal flu or pneumonia”

      Most who die are not seriously ill. They may have dangerous conditions, but they are not acutely dying of them. And, most would not die from the seasonal flu. To assert otherwise is to ignore the massive increase in all-cause deaths under COVID – in many countries.

      “C-19 is not a problem for the young and healthy herd. Mother Nature and her buddy Grim Reaper are just doing their jobs, culling the herd of the too many, too old, too sick warehoused too close together as Medicare/Medicaid cash cows in poorly run contagious lethal elder care facilities.

      The average COVID19 death results in a 10 year loss of life, compared to no COVID19. Furthermore, many of the vulnerable are not in elder care facilities, and many are working or living with those who need to work.

      But in any case, your argument is remarkably sociopathic. Yeah, let’s just let Mother Nature cull the herd.

      I am disgusted.

      • Joe - the non epidemiologist

        Nickrealty comment – “In other words: If you are already seriously ill, C-19 will probably finish you off, i.e. no different from the seasonal flu or pneumonia”

        Meso’s response – “Most who die are not seriously ill. They may have dangerous conditions, but they are not acutely dying of them.”

        both comments are partly correct. The most recent stats that I could locate was from 2012-2013, which indicated the median (not average) life expectancy for a male entering a nursing home was 3-4 months and the median life expectancy for female was 7 months. I couldnt find the median life expectancy for 2018-2019 though the average jumped to approx 24 months from an average life expectancy of approx 15 months in the 2012 time frame. Basically, a third to half of the individuals who enter a nursing home go there to die. From that standpoint, Nick’s comment is correct.

        On the other hand, one half or more are in LTC for the assisted living aspect which makes Meso’s comment correct.

        Unfortunately, the data for who dies in nursing homes from covid or with covid is lumped into the broader category of Long term care, which makes distinquishing the difference impractical.

      • “On the other hand, one half or more are in LTC for the assisted living aspect which makes Meso’s comment correct. ”

        Thanks, but you missed an important group – the large number of elderly who are not in LTC at all. That doesn’t mean they don’t have comorbidities, it just means they don’t need to be in a facility. I know far more in the risk category who live outside LTC than who live inside.

      • It’s anecdotal but my brother reports that the typical covid death in his system is a very obese person in their 70s or 80s. Being very obese is a life threatening condition because you almost certainly have high blood pressure, diabetes, and often quite high blood lipids. This makes you much more likely to have a heart attack just to name one thing.

        I’ve been doing extensive research on this topic in my quest to improve my insulin sensitivity and most people don’t realize how powerful large weight losses are for arresting these metabolic disorders.

        One reason why US death rates are so high is probably because America is in the throes of an obesity and diabetes epidemic. Swedes on the other hand have much lower obesity rates.

        In short, these so called “non serious” comorbidities are in fact very serious and often life threatening on their own. They are also quite common among the elderly in the US.

      • > Swedes on the other hand have much lower obesity rates.

        US PFR = 0.12%, Sweden = 0.092%

        Considering how Sweden should be way better at controlling for COVID reality for many reasons, the relative prevalence of obesity in the two countries seems unlikely to be a terribly explantory variable.

      • Josh, you doubt most true statements. You have no evidence. Mine is very reliable although anecdotal.

  37. UK-Weather Lass

    It is a good news day in the UK with the first Astra Zeneka vaccination. However, that is totally shafted by Government threats of more extreme restrictions driven, I assume, by the continued ability of the variant SARS-CoV-2, known about since early autumn, to confound all attempt to suppress it via more stringent restrictions. How extreme can you make restrictions before the penny drops and it is realised that something we are doing isn’t working the way it was envisioned by expert scientists and lay politicians?

    Does the answer lie in the fact that in spite of having had almost a year to ratchet up resources in our NHS nothing has been done by Government to do so, and our ‘famed’ Nightingale Hospitals are no longer regarded as potential spare hospital capacity but instead are now possible potential mass vaccination sites. Rather than blame people for not spacing, facing, and washing, how about asking serious questions of Government ministers and their experts who are failing to make good choices of policy with effective outcomes.

    Out testing regime is poor (too little expertise). Out tracing regime is poor (too little experience). The data emerging from these will therefore be unreliable to say the least (made up as they go along). Why are the genuine criticisms of these facts being ignored by those in charge and when is this going to be tackled by all our media and the people who have had their livelihoods unnecessarily destroyed given some hope for the future?

  38. David Wojick

    Regarding the $542/kWh 232 kWh powerwall, there is also the cost of hooking and running millions of them together and housing them. EIA reports that even the tiny 50 MWh utility scale battery systems we are building today average around $1500/kWh. New York City would need over 3 million MWh or 12 million powerwalls working together. The scale is staggering!.

    Tesla has built a few systems for $500/kWh but I think these must be loss leaders. Tesla can afford to sell a bunch for a fraction of cost in order to become the market leader.

  39. This was Australia during SARS, which was a far deadlier than COVID19. You would have been fined for being “sciency” on masks!

    —-
    Retailers who cash in on community fears about SARS by exaggerating the health benefits of surgical masks could face fines of up to $110,000.

    NSW Fair Trading Minister Reba Meagher yesterday warned that distributors and traders could be prosecuted if it was suggested the masks offered unrealistic levels of protection from the disease.

    “I’m sure everyone would agree that it is un-Australian to profiteer from people’s fears and anxieties,” Ms Meagher said.

    “There appears to be some debate about whether surgical masks are able to minimise the effects of SARS.”

    Ms Meagher said her department would investigate any complaints about false mask claims which concerned the public.
    —-
    https://amp.smh.com.au/national/farce-mask-its-safe-for-only-20-minutes-20030427-gdgnyo.html

    • Cheby –

      News bulletin: Things change.

      You should be glad that they do.

    • Chebysky and Bali: Masks and other PPE have been used to protect doctors and nurses from COVID and other respiratory illnesses in hospitals. Much research has been done. There is no doubt their PPE works. Unfortunately we don’t have the capability of providing that level of protection to ordinary citizens.

      Until COVID came along, there wasn’t much of a need to protect the public from respiratory viruses using masks. Studies with volunteers wearing surgical masks to prevent influenza on college campuses and in homes showed that masks provided significant protect to those who wore them, but fear of influenza didn’t provide much motivation to wear them. In public health, compliance is as important as efficacy. (A drug whose side effects cause most patients to stop taking it is as worthless as a drug with no efficacy.) If ordinary citizens weren’t being misled by conspiracy theorists like you, fear of COVID and the damage it is doing to our economy and lifestyle should provide an appropriate incentive to wear masks.

      The efficacy of masks is complicated by the fact that there are two major modes of transmission of COVID: a) droplets that are sprayed by coughing, talking, etc. and b) aerosols that can remain can remain suspended and infectious in the air for hours. Cigarette smoke is an aerosol and if you can smell someone’s smoke, they can infect you. (Unfortunately, the smell of cigarettes is deposited on surfaces where it lingers longer than the aerosols.) Almost any mask will block droplets. Aerosols pass through ordinary cloth masks fairly easily unless they contain a blown polypropylene layer like surgical masks. This is why:

      “Retailers who cash in on community fears about SARS by exaggerating the health benefits of surgical masks could face fines of up to $110,000.”

      Some people may be misled into thinking that masks will provide 100% protection and be encouraged to engage in risky behavior. The other problem is that the N95 masks that are used in hospitals are held tightly to the face by powerful elastic bands and are carefully checked for fit by professionals. The masks worn by the public allow aerosols to leak around the edges and through the fabric to various extents depending on fit. You can buy masks made out of materials with a better PFE (particle filtration efficiency), but between leakage, deterioration with use and washing, it isn’t clear that ordinary people can cut their risk of infection or transmission by aerosols by much more than 50%. So the authorities are focusing on getting people to wear any kind of mask and block transmissions by droplets (by consensus the major route of transmission) and ignoring the far more challenging problem of getting people to use masks that are more effective against aerosols.

      Universal use of cloth masks in theory should cut transmission by at least 50%, which would be enough to end to end the pandemic in most countries. Since every surge we have seen so far – including those in North Dakota and Belgium where 1% of the populations was testing positive every week – appears to have ended well short of herd immunity, we know that something has caused surges to end. Perhaps when hospitals are overflowing, people are finally motivated enough to wear masks.

    • This article is mostly bad joke by conspiracy theorists designed to reduce public trust in the scientific experts we need to fight this pandemic – the same scientific experts who have created vaccines with the potential to end this pandemic. Some particulars:

      PCR assays are NOT intended to prove who is and who isn’t infectious. Assays needed to determine the presence of infectious virus must be run special laboratories and are totally unsuitable for mass testing. PCR assays detect the presence of full-length OR fragmented viral nucleic acids. The number of cycles of amplification needed to produce a detectable signal provides a rough estimate of how much viral nucleic acid (“viral load” or “viral titer”) was present in a patient’s sample. A small viral load could mean that someone was infected three days ago and is not yet infectious, but WILL BE INFECTIOUS in a day or two – and it takes a few days to get results back. It is well known that viral nucleic acids (probably mostly fragmented) can be detected for many days after a person is no longer considered to be infectious. The CDC’s current guidelines for patients and health care workers returning to normal activity after a positive test are based on disappearance of symptoms in symptomatic patients and time in asymptomatic patients. They don’t require a negative PCR test.

      The first link in the first sentence about FALSE RESULTS refers to mistakes personnel make in collecting samples from patients, not to false results from the PCR assay itself. Contamination of patient samples with the target nucleic acids in the laboratory is a well known problem with PCR assays, especially when many cycles of amplification are run. Every assay includes positive and negative controls intended to detect systematic contamination and other problems. Although no assay is 100% reliable, PCR assays are highly reproducible.

    • Cheby –

      This nonsense about “false positive” is false. And not remotely positive. You really ought to stop spreading nonsense. It isn’t good for anyone when you do that:

      >> And we can see this incredible accuracy happening in real life. In Australia, despite hundreds of thousands of tests conducted every week, there are vanishingly few positive results. In New South Wales, the state that I live in, we conduct more than 115,000 tests every week with <40 positive results. Even if every one of those were a false positive, the false positive rate would still be less than a fraction of 0.1%.

      https://gidmk.medium.com/most-positive-coronavirus-tests-are-true-positives-60c95fe54fec

  40. UK new covid variant detected in New York and Western Australia.

    UK in full lockdown until vaccinations rolled out, which is 3-4 months minimum.

    France has a potential big problem in that vaccinations are at a snail’s pace due to the people having the right to refuse the jab.

    I predict France will be forced to abandon the lockdown-til-vacination strategy and open up the economy with those at high risk taking their own precautions.

  41. Here is none other than NYT discussing about manufacturing fake epidemics using fast unreliable tests like PCR:

    • Cheby –

      The morbidity and mortality we’re seeing goes in parallel with the # of positive tests.

      The PCR test is not the right test for surveillance, but this isn’t some kind of pandemic that isn’t. This meme that it’s a “casedemic” is false. The “false positives” meme is false.

      >> And we can see this incredible accuracy happening in real life. In Australia, despite hundreds of thousands of tests conducted every week, there are vanishingly few positive results. In New South Wales, the state that I live in, we conduct more than 115,000 tests every week with <40 positive results. Even if every one of those were a false positive, the false positive rate would still be less than a fraction of 0.1%.

      https://gidmk.medium.com/most-positive-coronavirus-tests-are-true-positives-60c95fe54fec

      You really out to stop with this nonsense. It's highly irresponsible.

      • Joshua – I have lived in and worked in NSW for a while. Miss the beaches :)

        “The morbidity and mortality we’re seeing goes in parallel with the # of positive tests.”

        This ought to be the case for ANY disease. I don’t see how this is a special insight.

        The point is that governments, PH bureaucracies and media have switched their bleating from death to hospital overrun to cases and it appears that the idea is to keep the deadly pandemic narrative alive in anyway possible.

        With less than 40 positive tests and even less deaths, why do you Australians still market this as a pandemic?

      • Cheby –

        > This ought to be the case for ANY disease. I don’t see how this is a special insight.

        Why are you expecting special insight? If course it isn’t “special insight.” It’s common sense. That was my point.

        > The point is that governments, PH bureaucracies and media have switched their bleating from death to hospital overrun to cases…

        You’re acting as if they can be decoupled. They can’t. That’s the point.

        >With less than 40 positive tests and even less deaths, why do you Australians still market this as a pandemic?

        I’m not Australian. I gave you the link. Read it.

        No one is “marketing” a pandemic. Don’t be paranoid.

      • Joshua: Here are some possible answers to questions you have raised:

        CFR = deaths/detected case. IFR = deaths/total cases. CRF/IFR = total cases/detected cases. total cases = seropositive

        Seropositivity surveys this spring suggested that we were missing about 10 cases for every for case we detected by PCR and CFR/IFR = 11. Now that cumulative detected cases have reached 14% of the total populations in some areas (and up to 20% in smaller locations that might be atypical, say with a prison), it is obvious that the early seropositivity surveys must have been wrong – possibly because of a higher false positive rate in the field than was established in the laboratory. This caused early workers to calculate an IFR similar to influenza and make the assertion that coronavirus was no more deadly than seasonal influenza. However, influenza kills a significant number of people only in the winter. We are now seeing just how deadly coronavirus can be in the winter – despite our best efforts to suppress it (that we never made for seasonal influenza). That deadliness is a function of both increased transmissibility and increased lethality per infection. Clearly we got a great deal wrong early in the pandemic.

        North Dakota today has 12+% cumulative infections (almost all this fall) and a death rate of 178/100,000, very close to that of NY, NJ, and MA before they began surging in the past month. However cumulative cases are only 5.5% in these three states. Therefore;

        CFR_spring = 2*CFR_fall

        If the IFR rate had remained constant, then:

        (CRF/IFR)_spring = 2*(CRF/IFR)_fall
        (total cases/det cases)_spring = 2*(total cases/det cases)_fall

        However, improved treatments and the falling age of those infected (as the vulnerable learned to protect themselves) means that:

        IFR_spring = X*IFR_fall
        (total cases/det cases)_spring = (2/X)*(total cases/det cases)_fall

        where X is a number greater than 1 that reflects the decreasing IFR due to better treatment. Therefore the ratio of total cases to detected cases has changed by less than a factor of 2. So, while we may want to assume that increased testing capacity has dramatically changed the factor that converts detected cases into total cases, this just isn’t true.

        In Yuma and Santa Cruz counties in AZ, 14.3% of the population has tested positive and the new cases are being detect at a near record rate 150-170 new cases/100,000/day = 0.15%-0.17% of population/day or 1+%/week. Clearly approaching herd immunity doesn’t appear to be playing a major role limiting the pandemic at the moment.

        If we think approaching herd immunity must slow the pandemic when 50% (?) of the people are immune, then we could be missing 2 cases (but probably not 3 cases) for every 1 we detect and still have a raging pandemic. And since we know there are asymptomatic infections and mildly symptomatic infections that never get tested, it would be surprising if we there were much less than 1 (?) undetected case for every detected case. Substitute your own estimates for the ?’s. So CFR/IFR is likely 2-3.

    • More unnecessary alarmism from conspiracy theorist Chebyshev. From the scientific article on this “false epidemic”. The idiots at the NYT didn’t report the whole story.

      In a previous study, environmental contamination from whole cell pertussis vaccines was found to be the cause of positive PCR results from patient specimens.7 Environmental investigation was performed in rooms at 2 different clinics where the vaccine was administered to the patients. B. pertussis PCR-positive material was detected on laboratory benches, steel tables, staff’s clothes, and skin of the hands of the staff in the vaccination room at both clinics. In the clinic where the vaccine administration and specimen collection for B. pertussis were separated by a great distance, patient specimens were culture negative and PCR-negative. However, in the clinic where the vaccinations were performed in closer proximity to the examination room, 91% of the patient specimens were PCR-positive and 66% of the specimens were culture-negative. In this situation, the whole cell pertussis vaccine was the cause of the contamination. The presence of DNA in whole cell vaccines is predictable. Depending on the method of antigen preparation in the acellular pertussis vaccines, the presence of residual DNA might also be predictable.

      https://journals.lww.com/pidj/FullText/2008/01000/Real_Time_Polymerase_Chain_Reaction_Detection_of.17.aspx

      In the absence of politicization, science is usually a self-correcting endeavor, though detecting and correcting problems can sometimes be challenging. (The existence of the IPCC, a political organization not run on scientific principles, makes climate science an exception to this generalization.) The fact that information from mistakes like this one is published and widely distributed is why the possibility that COVID mRNA vaccines could contaminate PCR and antibody assays has undoubtably been considered. This is one reason that the FDA reviews data real labs trying out new tests before they license them for sale.

      https://www.turnto23.com/news/coronavirus/doctor-covid-vaccine-wont-cause-false-positive-results

      What isn’t self-correcting are conspiracy theories spread by social media. There is a pandemic of conspiracy theories that – in the long run – could cause far more damage than COVID. Extremists on both sides are destroying public confidence in our police (BLM), historical heritage (1619 Project), FBI, elections, rule of law, etc.

  42. Science magazine has a useful review on increased transmissibility of some variants.

    https://science.sciencemag.org/content/371/6524/9?utm_source=Nature+Briefing&utm_campaign=bc64e831c1-briefing-dy-20210104&utm_medium=email&utm_term=0_c9dfd39373-bc64e831c1-43368041

    The spike protein in some variants is predicted to bind more tightly to the ACE receptor. However, affinity for the ACE receptor is unimportant if bound virus is internalized faster than it dissociates from the ACE receptor. The rate at which the virus reaches an ACE receptor is controlled by diffusion, which is the same for all variants. There is an on-rate for binding to the receptor and an off-rate for dissociation from the receptor and affinity is the ratio of the on- and off-rate constants.

    The article says: “Gupta also engineered a lentivirus to express mutated versions of SARS-CoV-2’s spike and found that the [69-70] deletion alone made the virus twice as infectious for human cells.” Here is a functional assay unambiguously demonstrating the importance of a particular mutation. Unfortunately, epidemiological data never involves variants with single mutations.

    “Yet exactly what impact each mutation has is much more difficult to assess than spotting them or showing they’re on the rise, says Seema Lakdawala, a biologist at the University of Pittsburgh.”

    “Animal experiments can help show an effect, but they have limitations. Hamsters already transmit SARS-CoV-2 virus rapidly, for instance, which could obscure any effect of the new variant. Ferrets transmit it less efficiently, so a difference may be more easily detectable, Lakdawala says. “But does that really translate to humans? I doubt it.” A definitive answer may be months off, she predicts.”

    Chemists are taught that the rate-limiting step in a series of reactions controls the rate of product formation. If the rate limiting step is gains entry to a human cell, then mutations effecting all later steps should be irrelevant. If the rate of replication of viral RNA is limiting, then mutations in both the rate of entry and the rate of replication could be important. Natural selection of fitter viruses can only occur by mutations that control the rate-limiting step.

  43. “No one is “marketing” a pandemic. Don’t be paranoid.”

    Joshua –
    Paranoid? Not at all. I have my cloth mask, which, according to the new advances in mask science as you highlighted, saves me from not only COVID19 but an assortment of similar or larger sized viruses. I feel like a superman.

    • Cheby –

      > I have my cloth mask, which, according to the new advances in mask science as you highlighted, saves me from not only COVID19…

      You should start paying attention. The benefit from you wearing a mask is primarily to protect others from you if you’re infectious.

      It isn’t all about you, Cheby.

      • Joshua –
        Oh yes. Just like a Superman saves others!
        I like how you threw in “primarily” there.

      • Cheby –

        Try paying attention. It isn’t about “saving” others. It’s about reducing the chances of you infecting others if you’re infectious. Yes, that is the primary reason for you to wear a mask.

        Primary.

        Glad you noticed that.

  44. Joshua –

    So, under your regime, everyone seems to be presumed sick (ie universal mask mandates).

    Is that a matter of convenience, lazy problem solving or there is some advanced science behind it?

    It also follows, under your regime, that you would be wearing mask all the time for the rest of your life? Who knows you could be sick at any given time? After all it is about others, ain’t it?

    Please bear with my limited reasoning capabilities. Most appreciated.

    Humbly yours,

    Chebyshev.

  45. China bans WHO team of experts to investigate source of covid-19, just a week before their departure. Suspicions of foul play only increase:

  46. The whole arguments about ‘infectivity’ really are incredibly ridiculous. Here are the basics of reality:

    1. For 99%+ of the population, becoming infected is a good thing: the body’s natural immune system will become activated and resistance will ensue until such time as a virus mutates sufficiently to warrant a new immune response being required.
    2. For the elderly, the immunocompromised and otherwise generally seriously unhealthy, the greater infectivity is a problem if the virulence is equal or greater to the initial strain.The evidence of previous epidemics the past 100 years is that in general, viruses mutate to become more infectious but LESS virulent as a strategy for viral replication. Nonetheless there is a justification in immunising such folks or asking the immunocompromised to take greater steps to prevent contact with healthy infected individuals.
    3. As it is, the only important data for governmental decisions are the excess number of deaths as compared to the 5-yearly means. The UK data for England and Wales is published by the Office for National Statistics on a weekly basis where registered deaths are concerned. The evidence is absolutely categorical that no crisis akin to the period of April 2020 has occurred since October the 1st in the UK, with the peak of excess deaths in late November 2020 representing a 20.8% excess death rate, with the latest figures of December 18th being 12.7% above average. Such an excess is entirely within normal variability and correlates with a cooler early December 2020 than in recent years (nothing excessive, mind you).

    Such data conclusively shows that either the UK government is dangerously incompetent and in need of removal from office; or they are willfully corrupt and malevolent, wasting literally tens of billions of pounds on futile track n trace + inadequately tested vaccines, whilst simultaneously torching the SME business ecosystem which employs upward of 10 million people in the UK.

    Not to put too fine a point on it, the opinions of Professors Neil Ferguson, Peter Horby should be discounted. The employment of Chris Whitty and Patrick Vallance should be terminated. And the Queen should dissolve Parliament to remove the completely corrupt and incompetent Government of Boris Johnson (we won’t go into the totally corrupt ‘procurement’ procedures seen for billions of pounds of UK Govt spending in 2020 which would shame a banana republic run by Bernie Madoff…) et al.

    • rtj1211 –

      I always love it when I get to meet the smartest person in the room.

      > 1. For 99%+ of the population, becoming infected is a good thing: the body’s natural immune system will become activated and resistance will ensue until such time as a virus mutates sufficiently to warrant a new immune response being required.

      A good thing as compared to what? While the number of people below 85, or 75, or even 65 who die from COVID is fairly low, the number of people who get significantly ill is much greater and even further, the number of people hospitalized is much greater. That isn’t a “good thing” in an absolute sense, but in a relative sense it’s obviously far less of a “good thing” than if they don’t get infected and we can establish “herd immunity” primarily through vaccination.

      >2. For the elderly, the immunocompromised and otherwise generally seriously unhealthy, the greater infectivity is a problem if the virulence is equal or greater to the initial strain.The evidence of previous epidemics the past 100 years is that in general, viruses mutate to become more infectious but LESS virulent as a strategy for viral replication.

      If you followed the discussion of this among people who actually study the related science – you will see that mostly all of them reject your assumption there. If you need it, I could dig out some links for you. But maybe yu should just try actually researching the issue?

      > 3. As it is, the only important data for governmental decisions are the excess number of deaths as compared to the 5-yearly means.

      Excess deaths is not a very good metric to use, as there are a lot of confounding factors.

      > The UK data for England and Wales is published by the Office for National Statistics on a weekly basis where registered deaths are concerned. The evidence is absolutely categorical that no crisis akin to the period of April 2020 has occurred since October the 1st in the UK,

      Once again, you shouldn’t be making statements such as that unless you have control for confounding factors (such as fewer deaths from the flu or other causes when people significantly reduce their activity levels). Perhaps you have it? In which case, please do let us know how you’re control for the confounding factors.

      > Such data conclusively shows that either the UK government is dangerously incompetent and in need of removal from office; or they are willfully corrupt and malevolent, wasting literally tens of billions of pounds on futile track n trace + inadequately tested vaccines, whilst simultaneously torching the SME business ecosystem which employs upward of 10 million people in the UK.

      Arguing from incredulity is a fallacy.

    • rtj1211 –

      I always love it when I get to meet the smartest person in the room.

      > 1. For 99%+ of the population, becoming infected is a good thing: the body’s natural immune system will become activated and resistance will ensue until such time as a virus mutates sufficiently to warrant a new immune response being required.

      A good thing as compared to what? While the number of people below 85, or 75, or even 65 who die from COVID is fairly low, the number of people who get significantly ill is much greater and even further, the number of people hospitalized is much greater. That isn’t a “good thing” in an absolute sense, but in a relative sense it’s obviously far less of a “good thing” than if they don’t get infected and we can establish “herd immunity” primarily through vaccination.

      • >2. For the elderly, the immunocompromised and otherwise generally seriously unhealthy, the greater infectivity is a problem if the virulence is equal or greater to the initial strain.The evidence of previous epidemics the past 100 years is that in general, viruses mutate to become more infectious but LESS virulent as a strategy for viral replication.

        If you followed the discussion of this among people who actually study the related science – you will see that mostly all of them reject your assumption there. If you need it, I could dig out some links for you. But maybe yu should just try actually researching the issue?

      • > 3. As it is, the only important data for governmental decisions are the excess number of deaths as compared to the 5-yearly means.

        Excess deaths is not a very good metric to use, as there are a lot of confounding factors.

      • Excess deaths is not a very good metric to use, as there are a lot of confounding factors.

        > The UK data for England and Wales is published by the Office for National Statistics on a weekly basis where registered deaths are concerned. The evidence is absolutely categorical that no crisis akin to the period of April 2020 has occurred since October the 1st in the UK,

        Once again, you shouldn’t be making statements such as that unless you have control for confounding factors (such as fewer deaths from the flu or other causes when people significantly reduce their activity levels). Perhaps you have it? In which case, please do let us know how you’re control for the confounding factors.

      • > The UK data …

        Once again, you shouldn’t be making statements such as that unless you have control for confounding factors (such as fewer deaths from the flu or other causes when people significantly reduce their activity levels). Perhaps you have it? In which case, please do let us know how you’re control for the confounding factors.

      • > Such data conclusively shows …

        Arguing from incredulity is a fallacy.

  47. EU member states has growing tensions over slow rollout of vaccinations. The UK is lucky to be out of the debacle:

  48. Brace yourselves for another worldwide pandemic with a 60% mortality rate in humans:

  49. Potential big problems ahead with vaccines not effective against new variant strains in UK:

    “However, transport minister Grant Shapps said there were fears that some vaccines might not work properly against a highly contagious variant of the coronavirus that has emerged in South Africa.

    “This is a very big concern for the scientists,” he told LBC radio.

    A laboratory study by the U.S. drugmaker Pfizer, not yet peer-reviewed, indicated that the vaccine it is making, developed by Germany’s BioNTech, does work against one key mutation in the new variants found in Britain and South Africa.”

    https://www.reuters.com/article/uk-health-coronavirus-britain/uk-minister-says-vaccine-might-not-work-against-safrican-variant-idUSKBN29D0S2

  50. Nic Lewis said this on August 17:
    “I likewise concluded that NYC reached herd immunity in April. I think London and Stockholm have also done so, and no doubt various other major cities as well. I view Stockholm as an important case study, since it never had a lockdown and behaviour now seems not to be too far off normal. The same goes for Geneva, save that it did have a lockdown originally.”
    https://www.nicholaslewis.org/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought-update/

    “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/

    As I and others have explained for months now, herd immunity is about non-mitigated baseline conditions of R0; i.e. no additional public health interventions and no additional behavior changes beyond what would have been present at about the same time of the year in 2019. So if those 5 regions above really reached the herd immunity threshold in March/April 2020, then immunity should be sufficient to keep R less than 1 in non-mitigated baseline conditions, let alone under the mitigated non-baseline situations that actually existed in those regions.

    So after April, no 2nd wave with no increase in cases/day:

    In reality, all 5 region had 2nd waves with increases in SARS-CoV-2 cases/day and COVID-19 deaths/day. In fact, Geneva’s 2nd wave in November wave was worse in terms of deaths/day than their 1st wave, let alone in terms of cases/day:

    Geneva:
    https://www.covid19.admin.ch/en/epidemiologic/death?detRel=abs&detTime=total&detGeo=GE

    Sweden:
    https://ourworldindata.org/coronavirus-data-explorer?zoomToSelection=true&time=earliest..latest&country=SWE~DNK~FIN~NOR~ISL&region=World&casesMetric=true&interval=smoothed&perCapita=true&smoothing=7&pickerMetric=location&pickerSort=asc

    Stockholm, Sweden:
    https://experience.arcgis.com/experience/19fc7e3f61ec4e86af178fe2275029c5/page/page_0/

    London:
    https://coronavirus.data.gov.uk/details/cases?areaType=region&areaName=London

    New York City:
    https://www1.nyc.gov/site/doh/covid/covid-19-data-trends.page#epicurve

    The “HIT is low” idea is thus deader than dead. Anyone still advocating it is either willfully ignorant, disingenuous, and/or ideologically-motivated to the point of crippling bias.

  51. Ivermectin as a well known super drug can be used to combat covid-19 but ignored by health authorities and WHO etc.

  52. The real question to be asked is quite simple: ‘what story line could the Establishment come up with to scare the uneducated population again?

    What is absolutely clear to anyone with an independent mind is that lockdown and economic catastrophe was the absolute alpha and omega of the billionaire elite. Bill Gates smirking back in spring 2020 about ‘people won’t laugh when a worse variant emerges’ gave the game away long ago.

    The variant isn’t worse, but it can be PORTAYED as worse, simply because it is NEW and UNCHARACTERISED. That justifies lockdowns on steroids by our utterly corrupt health minister Matthew Hancock.

    If people want to overcome this economic arson, they need to always start from the assumption that mischief is afoot.

    • Good point.

      Conspiracy theories w/o any actual supporting evidence are so great at explaining everything so completely.

    • Hopefully one of these days Nic will get something right about COVID.

      -snip-
      GTF cases (0.1%) and 104 deaths among SGTF cases (0.2%), within 28 days of specimen date. With this, the risk ratio increased to 1.65 (95%CI 1.21-2.25
      -snip-

  53. An interesting paper on using PCR cycle threshold counts as a way to estimate the trajectory of an epidemic: https://www.medrxiv.org/content/10.1101/2020.10.08.20204222v2