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Great article on misconceptions about herd immunity to COVID19

  • 1.  Great article on misconceptions about herd immunity to COVID19

    Posted 05-07-2020 10:01

    This article is a 2-minute read and clears up a lot of epidemiological misconceptions about COVID19.  

    Early Herd Immunity against COVID-19: A Dangerous Misconception

    David Dowdy, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health
    Gypsyamber D'Souza, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health

    "As infectious disease epidemiologists, we wish to state clearly that herd immunity against COVID-19 will not be achieved at a population level in 2020, barring a public health catastrophe."

    https://coronavirus.jhu.edu/from-our-experts/early-herd-immunity-against-covid-19-a-dangerous-misconception?fbclid=IwAR0GAXZaJCYr2WIpLO7WSq2GJDbfSdYnAyNID5PwkXIujgzRsnPE3A-t1sM

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    Deirdre Middleton, MPH
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  • 2.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-08-2020 10:37
    Edited by Sven Serneels 05-08-2020 18:42
    I have noticed that some other threads on COVID-19 have gotten highly emotional and political, which is not what ASA Connect is meant for. I do not intend to ignite any such discussion here. However, from a professional perspective, I can only disagree with Deirdre's opinion on this article. In its present state, it is poor science. 

    The article is nothing more than an opinion piece. It makes statements such as "with over 25,000 confirmed cases a day – it will be well into 2021 before we reach herd immunity". This is essentially what we in this forum would call a "naive forecast": just taking the last value of the time series as the forecast for all future cases. In other threads, more sophisticated models are discussed, which put this approach into ridicule. 

    Furthermore, some assumptions are hardly defensible. In the forecast, they use the confirmed cases a day as the metric to estimate future developments, whereas just a paragraph earlier they admit that the number of real infections is orders of magnitude higher. Actually an estimate from LA county, meanwhile dated by a few weeks, estimates the number of real cases at that time to be 28 to 55 times higher than the confirmed cases: 

    https://news.usc.edu/168987/antibody-testing-results-covid-19-infections-los-angeles-county/

    There is obviously a difference between our densely populated areas and different onset times across the country, but not taking this information into account and using a naive forecast corresponds to some of the poorest data science I've seen reported in the media in recent times. 




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    Sven Serneels
    (Diretor, Data Science)
    -posting as a private person-
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    Original Message


  • 3.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 07:29
    Considering the controversy surrounding the USC and Stanford antibody testing studies (study design, sample size, false positive rate, not peer-reviewed, etc), I would recommend caution in using them to try and support your stance until further validation is done.

    https://www.theguardian.com/world/2020/apr/23/coronavirus-antibody-studies-california-stanford

    https://www.wired.com/story/new-covid-19-antibody-study-results-are-in-are-they-right/

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    Felix Mbuga
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    Original Message


  • 4.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 07:55
    Hi, Sven:

    You make some good points, but you may want to take another look at that LA article that found very high rates. Isn't that the one that later was badly challenged on the grounds that testing for a rather rare disease with an imperfect test can yield more false positives than real ones?  A specificity even a few percentage points below 100 (as seems likely) would explain their high rate.

    Ed

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    Edward Gracely
    Drexel University
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    Original Message


  • 5.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 08:12
    Dear All:

    I have been following the controversy regarding the Santa Clara and the Los Angeles County study.  I am not an epidemiologist, but rather a social scientist with both survey methods and demographic expertise.  The comments on MedXArchive (where at least two versions of a pre-print from the authors has been posted) really raise a lot of questions about this work and how it can be used to justify basically a reopening.  There is a very simple note that ran in the Washington Post the other day, which shows that using only confirmed cases of the flu versus Covid, there already more than 8 times the number of Covid deaths than flu deaths.

    The notion that these studies from CA are not politically driven is belied by the fact that one of the investigators went on Tucker Carlson before the research was finished.  Nor do they indicate where there funding came from, but a very coy about "a large number of donors."

    As with some other recent controversies (the employment rate under Obama and Trump pre-Pandemic, the Census Citizenship Questions) these numbers are highly politicized.  If one assumes, as seems reasonable the number in NYC, which gets the infection rate to about 10 times the confirmed 20 percent versus 2 percent, one gets to a IFR of about 0.5 percent.  Blow that up to what would be needed for herd immunity (say 60 or so %) and the back of my envelope gets to about 1 million deaths total.

    Andy

     https://www.washingtonpost.com/business/2020/05/02/theres-more-accurate-way-compare-coronavirus-deaths-flu/

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    Andrew Beveridge
    Professor of Sociology/ President, Social Explorer
    Queens and Grad Center CUNY and Social Explorer, Inc
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    Original Message


  • 6.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 11:09
    Dear All, 

    At first, I would like to respond to Felix and Edward. The Santa Clara and LA county studies were the first studies to emerge in this context. The design and practical setup of any study can be questioned. However, several studies have meanwhile followed suit, and all have one result in common: the actual number of infections is higher than the officially reported number of cases by not just a bit, but by an order of magnitude. This pattern seems to consistently reproduce in dense (sub)urban early infected areas. Not to account for this at all, as the press release that started off this thread did, is a much graver scientific error than to use these numbers with precaution. For instance, to assume wide-tailed priors could be justified. 

    Secondly, I would like to reply to Andy. In this context, every word seems to be politicized and it should not be, because there are very grave consequences either way. Given the circumstances, we will have to work in a politicized context. But again, a scientific result being politicized is a very weak argument to not account for it. The numbers Andy mentions are ballpark reproducible and recommend caution. However, some remarks that can be made here. The NYC data do present one of the best samples we have around the country. Yet the results present NYC as an outlier in many COVID related statistics. Do these results not generalize to other parts of the country because of lack of testing, or because of different factors influencing them such as demographics and population density? Likely a mix of both, but we don't know. Secondly, the article that started the thread intends to make a forecast. Which reason do we have to assume that the IFR will remain constant over time? I think it is reasonable to assume that the IFR will start dropping, as sadly the most vulnerable have already lost out. We can only assume a constant IFR as soon as there are sufficient longitudinal data, which we presently do not have. 


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    Sven Serneels
    Director, Data Analytics
    .: posting as a private person :.
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    Original Message


  • 7.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 11:26
    Dear All:

    I would suggest reading Gelman's analysis of the Santa Clara study, which is here along with comments.  https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ 

    A major point he made is that the Doctors did not consult with survey researchers (e.g., Is drawing from Facebook representative?  Was the wife of the PIs solicitation message accurate?) did not explain how they adjusted their sample to the population in Santa Clara.  Did not adjust for underreporting by age.  Did not explain how they adjusted by zip code.  Gelman also points out correctly that leading Survey Researchers are on the Stanford faculty.  Gelman is a leading Bayesian statistician.  

    The LA counterpart to the Santa Clara study was used by Rush Limbaugh to claim the LA or CA was at herd immunity.  One of the authors went on the well known science show Tucker Carlson.  Exactly who were the unnamed donors to the Stanford Study.  Inquiring minds want to known.

    Projecting their survey to NYC means that about 5.4 million people were infected in NYC.  The estimate from the NYC antibody study was much lower about 1.6 million give or take.  The raw deaths from flu in the US this year is about 8,000 the raw deaths from Covid so-far is about 80,000 and climbing.

    Covid is not the flu, we do not need very much to understand that fact.  The question is not that the data should not be politicized, of course it should not.  The question is can a study like the one in Santa Clara be trusted with any conclustion except that there is a quite low level of infection in Santa Clara.

    Andy


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    Andrew Beveridge
    Professor of Sociology/ President, Social Explorer
    Queens and Grad Center CUNY and Social Explorer, Inc
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    Original Message


  • 8.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 11:32
    Let me first state that I do not know the answers. And that I felt like the original article did not have any political agenda.

    @Sven Serneels​, Here is and excerpt from your last post: 
    I think it is reasonable to assume that the IFR will start dropping, as sadly the most vulnerable have already lost out. We can only assume a constant IFR as soon as there are sufficient longitudinal data, which we presently do not have. 

    Where is the science to support your statement?
    "I think it is reasonable to assume that the IFR will start dropping, as sadly the most vulnerable have already lost out."

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    Wilma Jackson
    Research Statistician Developer
    SAS Institute, Inc.
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    Original Message


  • 9.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 13:02
    I would appreciate having more science too. Today, it is just an assumption that I consider reasonable. 

    To test this assumption on a data driven basis for the present pandemic, will only become possible as time passes. I do not see an easy other route to get a data driven basis: e.g. one could use the data from the 1918-1919 pandemic. However, it would require a daily or at least monthly timeseries of IFR. I don't know if those data even exist. Anyone who could point us to them, feel free to help out. 

    I am well aware that it is common practice in many publications to assume IFR constant. But those publications typically focus on how well established diseases evolve, not on the outbreak of a novel disease that no patient's immune system was prepared for. Therefore, these constant IFRs are assumed at a point in time where it already has become reasonable to do so. Any representative time series data would be welcome. 

     


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    Sven Serneels
    Director, Data Analytics
    .: posting as a private person :.
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    Original Message


  • 10.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-12-2020 15:39
    ​While Sven Semeeds reckoning about the infection fatality rate (IFR) decreasing over time is speculative at the present, it does seem reasonable model but makes the following assumptions:
    1)  There are differential IFR rates in different segments of the population.  (This seems to have been the belief from the beginning, seniors with pre-existing conditions were assumed to be more vulnerable than younger healthy people without pre-existing conditions.)
    2)  Members of the segments with the higher rates are more likely to succumb to the disease
    3)  The likelihood of being exposed is approximately equal across segments.  (This is the primary area where there could be modification in the rates if these more vulnerable segments could be better protected in the long term.)

    The surviving population weighted average of these IFR within segments will produce a rate that will tend toward the lower rates over time as there are relatively fewer survivors in the higher IFR segments.

    However, there is a caveat that complicates this naïve model, and that is growth of the segments.  If the growth of a segment outstrips the death rate in that segment, the IFR rate could actually increase over time.  Over the course of life people move from one segment to another depending on health and chronic (or acute) comorbid conditions.  We do not know whether higher IFR segments in the population are growing fast enough to maintain or increase their relative proportions in the overall population weighted average.

    If you think that the transition into the higher IFR segments is not as fast as the death rates, then it would be reasonable to anticipate the population weighted IFR would decline over time.



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    Raoul Burchette
    Biostatistician
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    Original Message


  • 11.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-12-2020 15:49
    ​One other footnote, my previous model assumes no change in the IFR for a segment.  If we develop a cure or efficacious treatment for the disease, that will completely change the game and the reduce infection fatality rates (possibly differentially) for each segment of the population, and hence the IFR would decline over time.  It is still possible that differential growth in the various IFR segments could slow the change in IFR if the impact of the intervention is limited.

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    Raoul Burchette
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    Original Message


  • 12.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 10:24
    The article you cited:

    news.usc.edu/168987/...

    "team estimates that approximately 4.1% of the county's adult population has an antibody to the virus. Adjusting this estimate for the statistical margin of error implies about 2.8% to 5.6% of the county's adult population has an antibody to the virus"

    seems very much in line with what the article that the original poster cited:

    "Although more than 2.5 million confirmed cases of COVID-19 have been reported worldwide, studies suggest that (as of early April 2020) no more than 2-4%3–5 of any country's population has been infected with SARS-CoV-2 (the coronavirus that causes COVID-19)."

     




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    Wilma Jackson
    Research Statistician Developer
    SAS Institute, Inc.
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    Original Message


  • 13.  RE: Great article on misconceptions about herd immunity to COVID19

    Posted 05-11-2020 13:20
    David Dowdy and Gypsyamber D'Souza's three- or four-paragraph comment on the Johns Hopkins website is a response to what they consider to be irresponsible claims in the media that California and other places have achieved or are close to herd immunity. They wrote that "As infectious disease epidemiologists, we wish to state clearly that herd immunity against COVID-19 will not be achieved at a population level in 2020, barring a public health catastrophe." 

    This comment certainly is not written for statisticians. It contains little in the way of detailed analysis, let alone a model for making reasonably accurate predictions of timing in a changing political landscape. FWIW, they do cite to "a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions [such as national lockdowns] across 11 European countries."

    But is their conclusion too dire? The estimates of SARS-CoV-2 infections on the order of 50 (or more) times the official numbers in California are interesting. Several statisticians have savagely criticized these estimates as miscalculated and as unwarranted given the imperfect sensitivity of the serological tests. However, the criticism may be overstated. So let's assume these estimates are correct. A 50-fold underestimate may sound shocking, but the denominator in the ratio is small, and the relevant parameter for the herd-immunity issue is the true prevalence (assuming, of course, that an immune response confers reasonably long-lasting immunity). Where are we today? The LA and Santa Clara county convenience sampling studies in April by the California researchers (used to produce the ratio of 50 so) give estimates of 2.8% to 5.6% and 2.5% to 4.2%, respectively, for the proportion of the population that has been infected. The highest raw number I have seen is 31.5% positive serologic tests administered to 200 passersby on a street corner in Chelsea, Massachusetts. Better designed studies are underway in various locations.

    Dowdy and D'Souza assert that "To reach herd immunity for COVID-19, likely 70% or more of the population would need to be immune." If this is correct, the gap between where we are and the herd-immunity level seems substantial. Of course, that is just a gut reaction, and I wish I could point to a professionally respectable, statistically defensible modelling effort that gives a more optimistic answer to the question of whether we are approaching herd immunity in 2020.

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    David Kaye
    http://www.personal.psu.edu/dhk3/index.htm
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    Original Message


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