Critics Say a Pair of California Antibody Studies Contain Critical Statistical Errors That Produced Implausible Results

Too many false positives, nonrandom study population, and infection fatality rates out of whack with other data, critics claim.


Two studies by researchers associated with Stanford University and the University of Southern California using antibody blood tests have estimated that many more people have been infected with the novel coronavirus that causes COVID-19 than confirmed diagnoses would indicate. How many more people? In the Santa Clara (Silicon Valley) study, the researchers estimated that coronavirus infections at the beginning of April were 50- to 85-fold more than the number of confirmed cases at that time. In the Los Angeles County study, they estimated the infection rate at 28 to 55 times higher than confirmed cases in that jurisdiction.

If true, these findings of vastly more widespread rates of infection would suggest that the disease is much less lethal than the crude case fatality rates suggest. (A point noted by me and other Reason colleagues in reporting on these studies.) Not surprisingly, these findings have proved quite controversial, particularly drawing the critical attention of statisticians from other institutions.

Since the Los Angeles County study has apparently not yet been published online, let's focus on the chief objections to the Santa Clara study. Those include arguments that (1) the prevalence rates among people tested for antibodies to coronavirus published in the study are mostly, or even entirely, very likely due to false positives; (2) the results are skewed because it was enriched with participants who were more likely to have been exposed to the virus than the general population of the county; and (3) that COVID-19 infections must be very widespread to produce the excess mortality seen in places like New York City, e.g, essentially most New Yorkers must already have been infected, suggesting an unprecedented level of contagiousness.

First, let's look at the problem of false positives. The researchers' blood test survey in Santa Clara County found that 1.5 percent (50 out of 3,330 people tested) were positive for the presence of antibodies to the coronavirus. So the question is, how many of the 50 positives they found might be false positives?

Critics like Columbia University statistician Andrew Gelman and Silicon Valley entrepreneur Balij Srinivasan focus on the sensitivity (true positive rate) and specificity (true negative rate) of the blood test used by the researchers in the Santa Clara study. Without going into detail, they argue that it is possible that the vast majority of the positives generated by the blood test used by the researchers could be false positives. On the other hand, the lead author of the Santa Clara study, Jay Bhattacharya, tells Science, "The argument that the test is not specific enough to detect real positives is deeply flawed."

Another problem critics allege specifically with the Santa Clara study is that the research participants were recruited via Facebook. One concern with using this recruitment method is that it might result in a group of county residents who signed up for testing because they feared that they may been exposed to the virus. Such non-random study recruitment could boost the number of positives tested, thus skewing later calculations of overall prevalence.

Finally, the researchers' estimate of an infection fatality rate (IFR) for COVID-19 of between 0.12 and 0.2 percent derived from their demographic adjustments to the raw rate of 1.5 percent positives suggests extremely high rates of infection and contagiousness. "In order to generate these thousands of excess deaths [from COVID-19} in just a few weeks with the very low infection fatality rate of 0.12–0.2% claimed in the paper, the virus would have to be wildly contagious," points out Srinivasan.

As I noted earlier, given the number of deaths in New York City from COVID-19 such a relatively low IFR would implausibly suggest that essentially every resident of the Big Apple has already been infected by the virus.

The researchers tell me via email that they are working to address these and other objections and will soon release a revised version of the Santa Clara study soon. Stay tuned.

NEXT: Here’s Why Rep. Justin Amash Opposes the CARES Act

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  1. Another problem critics allege specifically with the Santa Clara study is that the research participants were recruited via Facebook.

    False positives from fake accounts?

    1. Sorry, Ron — couldn’t resist!

      I eagerly await the updated study.

    2. Sample bias is obviously an enormous problem when you’re estimating population infection rates.

      Note that the Powers That Be were not shy about using the Santa Clara study to support The Narrative despite a methodological flaw that would normally have them screeching about violations of their cargo cult statistics.

      Just goes to show, you always have to read the study yourself, because News is Propaganda.

      1. The normal method of doing this study would be to recruit College undergraduates from your University and extrapolate to the public at Large.

        So there is that.

        1. Very true, and is one reason why so many non-clinical psychology studies are bunkus. The key to science is replicability. Find something interesting? Go find it again! A student-based study isn’t worthless, but any student-based study needs to be followed up with a better sample set. “Hey, we might have found something, let’s get some better data and check again”.

          Unfortunately, to the media and world at large, publication in a journal means Truuf!

          p.s. I have a friend who routinely checks the statistical analysis in published studies. Weird hobby of his. I just don’t understand math geeks. Anyway, he finds a surprisingly large amount of mistakes.

    3. I have a hard time why they’re getting criticized for their sampling methodology, when the numbers in the dominant reporting have a methodology of ‘testing only for people with severe symptoms that match covid-19’. That people who think they might be infected respond with higher frequency to a study like this is vastly less biased than the current testing paradigm.

      1. This study is flawed, but not as flawed as all the other studies.

        The one valid concern is with the false positive rate of the test used. E.g., if the actual incidence is 0.01% and the false positive rate is 1.5%, the test results will show an incidence of 1.51%.

        I’d like to see this study repeated in cities with a high per capita death rate like NYC, New Orleans, and Detroit. The true incidence rate here might be far higher than the false positive rate.

  2. It seems we can’t get any proper study anymore. Won’t Science save us?

    1. Sorry, all real scientists are busy correcting their global climate warning change models to show we are all still going to die even though the fascists took over the whole economy.

      1. This must be the point where we all laugh because it’s so obviously a joke.

        1. If I wasn’t wearing a mask, do you think I would be smiling?

    2. There’s many proper studies out there, just they may not confirm your preexisting biases. The only reason people jumped on this one is that it let them say “I was right, COVID-19 was no big deal”.

      1. I don’t have a dog in the fight. I haven’t seen any study that didn’t get ripped apart from the “other side”. I’d love to see proper studies if you have links.

        1. It cannot possible be available until after the crisis, because before then we only have incomplete data.

          1. Yet you still call it a “crisis,” without all the data.

            1. The crisis is fascism, not C19.

              1. True.

          2. Here’s some crisis data for ya.
            A survey released Thursday by the James Beard Association found independent restaurants laid off 91% of their hourly employees and nearly 70% of salaried employees as of April 13 – double-digit increases in both categories since March. The poll of 1,400 small and independent restaurants found 38% of have closed temporarily or permanently, and 77% have seen their sales drop in half or worse.
            Perhaps most troubling: 28% of restaurants said they don’t believe they can survive another month of closure, and only 1 out of 5 are certain they can sustain their businesses until normal operations can resume.
            Gym chain 24 Hour Fitness is working with advisors at investment bank Lazard and law firm Weil, Gotshal & Manges to weigh options including a bankruptcy that could come as soon as the next few months, people familiar with the matter tell CNBC.
            The chain is grappling with a heavy debt load, deteriorating performance and a coronavirus pandemic that forced it to shut its more than 400 clubs.
            Neiman Marcus Group, one of the largest retailers in the United States, is reportedly ready to file bankruptcy amid the COVD-19 pandemic after defaulting millions in bond payments last week and furloughing 14,000 employees.
            Neiman Marcus would become the first major US department store to crumble amidst the economic set backs from the coronavirus outbreak.
            Indefinite furloughs began this weekend for more than 100,000 Disney, Best Buy and CarMax workers as businesses make cuts to survive the coronavirus pandemic and subsequent mandatory closures.

            1. Yet no talk of flattening that curve.

            2. let’s not forget the oil companies either. They’re about to take a hit, and then so will everyone connected to them.

  3. >>with the novel coronavirus

    why is it novel? this descriptor is everywhere

    1. It’s new (compared to other coronaviruses).

      I also think it’s a pretty stupid name FWIW.

    2. because it’s the virus that you to finally finish that novel because you’re locked down with nothing else to do forever

      1. *allows you to

    3. “Novel” means it’s new. We had Corona Viruses before. But COVID-19 (Corona Virus Disease discovered in 2019) is new, thus novel. And thus much more dangerous because there’s no immunity built up in the population.

  4. Or is it because they contradict their doomsday models?
    Inquiring minds want to know . My model , on the other
    hand , is a pic of a young Linda Carter in her Wonder
    Women outfit.

    1. Expect the next round of stimulus measures to include the costs of providing everyone a free memory hole.

  5. “Gentlemen, you took your foot off the panic peddle a bit too quickly for our tastes. We haven’t quite reached our destination.”

  6. //”In order to generate these thousands of excess deaths [from COVID-19} in just a few weeks with the very low infection fatality rate of 0.12–0.2% claimed in the paper, the virus would have to be wildly contagious,” points out Srinivasan.//

    So, which is it? Is the virus wildly contagious and a nuisance, or not all that contagious and a slightly larger nuisance?

    Further, if the virus is not all that contagious, why the fuck are playing the lockdown game?

    1. This.
      I though the virus was wildly contagious.

      1. Only when it comes to panicking and making sure the economy stays closed. When it comes to refuting a study which necessarily downplays their panic by suggesting the death rate is really low, then it’s okay to badmouth the idea that the virus is contagious.

        1. It’s contagious enough for you to stay in, but not contagious enough to spread. And to many people, that makes perfect fucking sense.

          The degree of doublethink is astounding. I really used to think Orwell was exaggerating his dystopian notions, but I am rapidly finding out that he was probably underestimating the capacity for human beings to delude themselves.

    2. New York is a mostly unique case. It’s incredibly dense with extremely high usage of mass transit. In addition, transit workers were ordered to no wear masks lest they spook the public.

      It would be quite easy for a diease to rapidly spread through New York, leading to much higher infection rate for the population.

      Santa Clara County, on the other hand, particularly the northern part where the study participants came from, is much less dense. It’s very sub-urban, with much less reliance on mass transit.

  7. So, how long is this novel

    1. Long enough to terminate its questions with question marks.

  8. Am I forgetting something, or have other studies done elsewhere also put the IFR on the same order of magnitude (0.3%-ish)?

    1. “With Amazon Prime your CDC Memory Hole is guaranteed to by delivered on Tuesday, November 3, 2020.”

      1. the same memory hole where all the trump quotes on hydroxychloroquine are located.

        1. I don’t think you understand how memory holes work.

          1. I don’t think you understand how holes work in general.

            1. Your mother would beg to differ. She’s an excellent pegger.

              1. um… I don’t think that word means what you think it means…

                1. Oh, I know. I know all about holes; all the holes.

        2. The same one where “we have to flatten the curve and allow hospitals time to prepare” went.

    2. Most studies I’ve seen have put the IFR between 0.5% and 1.0%. I think there’s values from 0.2% to 1.5% are still technically plausible, though less likely.

      Indeed if you redo the analysis of this study using Bayesian analysis, you get a 95% credible interval for the IFR of [0.3%, 1.1%].

      I’d be interested in reading the study that puts the number at 0.3%.

      1. If you’re doing a Bayesian analysis, what priors do you use?

        1. He doesn’t know because he read that somewhere amd copied it without understanding it

      2. Given the raw data aren’t publicly available as far as I know, I’m not sure how you performed the Bayesian analysis, or any analysis.

    3. There was a german serology study that estimated 0.37%.

  9. All the studies are flawed if they disagree with your political goals.
    Doesn’t matter what the infection rates or death rates are, some people will get sick and some wont. Some of the sick people will die and some won’t. If nothing was done beyond unending PSA’s about hand washing and anti-social distancing, even the most outrageous of the made up studies predict less damage to the country as a whole than what we have done.

    1. Yup. We allowed them to screw us royally.

  10. Can’t help but think we’re chasing a red herring here.

    The people of California who wish to go to work, open their businesses, or patronize those businesses should be free to do so–regardless of the results of any study. Anybody who wants to make their decision about whether to interact with others based on the results of this study should care about the results, but those who don’t care about the results of this study should be free to go to work, open their businesses, or patronize those businesses anyway.

    Let’s not get distracted.

    Your qualitative preference for safety from a virus is no more authoritative for being wrapped up in a scientific study about the lethality or preponderance of the virus than my qualitative preference for less unemployment–which is apparently approaching 16.4%*, nationally, and will continue to get worse as time as goes on. Should the accuracy of my statistics make any difference if I wanted to make it illegal for people to isolate themselves?

    *Chief US Economist for Morgan Stanley

    People used to argue about whether Saddam Hussein had WMD–as if it were a proxy for whether we should bomb, invade, and occupy Iraq. The fact was that bombing, invading, and occupying Iraq was a bad idea–regardless of whether Saddam Hussein had WMD.

    There are people who report the effects of global warming on polar bears–as if the impact of global warming on polar bears were more important than the impact of taxing fossil fuels on our standard of living. The fact is that some people care more about their own standard of living than they do about polar bears or the environment regardless of whether the use of fossil fuels has a negative impact on polar bear populations–and there isn’t anything wrong with that.

    People who fear losing their jobs, their businesses, or their homes more than they fear dying from COVID-19 should be free to open their businesses or go back to work–and that’s regardless of whether the results of this study are precise or inaccurate. The assumptions each of us make about the relative importance of various considerations does not necessarily match other people’s priorities, which is why each of us should be free to make choices for ourselves–regardless of whether the results of any study are precise or inaccurate.

    1. Excellent post.

      Ultimately, the studies do not matter. We do not need perfect information to make individual decisions. We will never have perfect information. There is no talisman out there from which to extract a perfect solution. Thus, as you stated so eloquently, “each of us should be free to make choices for ourselves.”

    2. Thank you! Well said.

    3. Exactly. The problem of trying to do completely “Science based policy” is that many important questions cannot be answered with science.

    4. Exactly right. Even if the worst case scenario had played out with millions dead this virus would not have destroyed the world economy. It was studies and experts and politicians that did that.

    5. Ken, you’re going to love this one. The Orange County (CA) Board of Supervisors yesterday voted to give cities the go-ahead to allow members of private golf courses to play, as long as they abide by the governor’s social distancing diktat. The clubs can’t “reopen”: pro shops and clubhouses remain closed. The players just walk on the course and play. No carts, no flagsticks, no bunker rakes, no anything from the clubs that players can touch. The mayor of Costa Mesa publicly announced her opposition, because it’s “not fair” to those who play at public courses. I pointed out to her that public courses are free to open under the same conditions, and more importantly, it shows a lack of appreciation for private property rights since the courses/players would not be in violation of any law. I asked her if she was really of the opinion that citizens shouldn’t be allowed to lawfully use their own assets whenever other citizens don’t own the same type of assets? Her response was “Are you really of the opinion that only people who can afford to recreate should be allowed to?” This passes for a logical argument from the mayor of an upscale city of over 110,000.

      1. These Karenfuehrers are doing a damn fine job of showing why Islam is right about women.

        1. “Karenfuehrer”

          Fn gold

      2. Jesus fuck, that kind of stupidity is terrifying.

    6. Yes. The Knowledge Problem is a real bitch.

      Unfortunately, those making decisions and threatening people with jail for having the temerity to put food on the table, don’t have any knowledge of the knowledge problem either.

  11. A lot of people have a vested interest in making sure we cower in fear. So any evidence to the contrary is going to be attacked.

  12. Well, this really shouldn’t be so hard to figure out – are the researchers or their critics the experts? Listen to the experts.

    1. We should just vote, and then do what we want anyway.

  13. Is it really so implausible that most people in New York have been exposed? Let’s say the virus was around for a month or more before the lockdowns. In a crowded city where lots of people use public transportation (and continued to after the locksdowns), many people are close to thousands of people every day. Nobody really noticed until old people started dying in droves.
    Seems plausible, at least.

    1. I mean, having commuted by subway every day until early March, it seems unsurprising that I would have been exposed. Even now, everyone is going to the grocery store and parks, so it wouldn’t surprise me if spread continued more or less unabated.

      1. As a New Yorker, none of this is inherently implausible. I distinctly recall sitting on subway cars in January/February with every other person coughing up a lung during the rush hour commute. No face masks, no distancing, none of that stuff.

        Frankly, in my experience after living for several decades in NYC, most winters you walk around with some mildly lingering bug or cold or flu-like thing for weeks at a time and you don’t even think anything of it, which was exactly the situation for me again when I got sick for two weeks in the end of March, except this time I went to a drive through testing facility and, voila, came up positive.

        Literally nothing was different, and I am fairly certain I get sick every year, sometimes multiple times, between October – April, from one thing or another. We have sufficient evidence to suggest that this SARS-COV-2 is very mild for 99% of people. Why is it so crazy to post that millions of people in NYC have already been through a wave, maybe more than one wave, and nobody even noticed?

        Well, I guess if you have an interest in perpetuating a panic, that kind of thinking tends to be inconvenient, or “implausible.”

        1. And here’s another thing.

          For years I worked up in Westchester and on Long Island and I drove to work. Then I got a new job in Manhattan around September 2014 and ditched the car for public transportation. That first year on subways for me was a fucking nightmare. It felt like I was catching something different every other week. The best way I can describe it is strong, lingering colds with lots of chest congestion. For a while there I thought, “fuck it, I am going to have to get a new job, because I cannot keep getting sick like this.” Sure enough, after that first winter season, I never experienced anything even remotely that severe and coast through flu season without any issues.

          If you can survive a NYC subway on the daily, chances are you can get through any type respiratory infection without a problem. And if you think you can avoid catching these bugs on the subway, you’re delusional. I would say even with the most stringent precautions, it is probably still impossible to avoid infection. The best you can hope for is a good immune system. That’s life.

        2. It isn’t crazy. It is likely and we will begin to see this over and over. You need to “believe” there isn’t herd immunity and that this is “deadly” so you’ll shut up and get your vaccine.
          Meanwhile we are all being immunized with Covid and have been for months.

        3. Wow. Have you obtained antibody testing yet? It would be interesting to see if it detected your Coronavirus antibodies.

    2. Let’s say the virus was around for a month or more before the lockdowns.

      And this isn’t an implausibly liberal t0. The recent ebola outbreak got from Bumfuck, Africa to Nowhere, TX in less than a week. The idea of something much less noticeable and much more passively contagious getting from Wuhan to NYC in less time isn’t unreal.

      1. The difference between Ebola and Covid is like night and day. Covid is a cold virus. Ebola is a hemorrhagic fever which is far more novel to most who would encounter it than this strain of a virus we DO normally encounter. It is harder to make antibody to Ebola and death is likely. Not so for Covid by a long shot.

  14. Statistician William M. Briggs posted a general discussion of this subject back on March 11.

  15. Why is it implausible that the vast majority of New York has been exposed/infected, but the death rate being over five percent seems totally plausible?

    And as Ken said, the plausibility doesn’t matter from a liberty perspective. Telling people they can’t earn a living or go outside (lets completely ignore that fresh air and sunlight are good for you no matter the virus dejure) is NEVER the appropriate response.

    1. Because that doesn’t happen with any other disease. Not every New Yorker gets the flu.

      1. Not every New Yorker will get BatCoof either, you moron.

      2. So isn’t it more likely that this particular disease is going to hit some places harder than others and even state wide bans aren’t the right solution?

      3. Chipper, you’re scientific understanding is as ignorant as every other understanding you push.

        The inference that a population sample from Santa Clara has to march on IFR with a population sample is idiotic. There are large swings when normalizing against populations. New york may in fact have a higher IFR than Santa Clara sonce they have higher pollution rates. This is something the critics of the study failed to eve consider.

        We already know that the vast majority of the deaths in NYC had an underlying medical condition. These critics didn’t even bother to try to normalize the numbers against prevalence of the major underlying conditions, relying almost solely on age. I can tell you right now, older people in the west tend to have healthier lifestyles than older people in NYC.

        The fact that Ronnie doesnt even posit this as an explanation shows he shouldn’t be ficking talking statistics. He committed basic flaws for comparative population studies. He tried to apply one population statistic to a completely different one.

        1. Yep. One of the more interesting ideas that I heard was that a lot of people have bad lungs from breathing air after 9/11. The responders got hit bad enough that we noticed then, but these people we’re just noticing now.

      4. Yes it does! If you actually think that you have to have been sick to have contacted and made antibody to a disease than I suggest picking up an immunology book. We’d all literally never last beyond age 2 if we were all so weak and unable to fight off basic infection that we literally encounter daily.

    2. It isn’t implausible. It’s actually extremely likely

    3. It’s implausible to me that anyone who rides NYC subways regularly hasn’t been exposed to COVID-19, as well as every other airborne pathogen affecting more than 0.1% of the population. That doesn’t mean they all caught it, but most of those who didn’t catch it must be resistant somehow. If there is no pre-existing resistance (which the alarmist models appear to have all assumed without evidence), then it seems plausible to me that most subway riders were infected weeks ago, and by now, any uninfected New Yorker is either very lucky or has been carefully avoiding contact not only with subway riders (including maids, wait staff, store clerks, and delivery persons), but also with those are in frequent contact with subway riders.

      And as others have mentioned, NYC is likely to have a IFR (infection fatality rate) higher than less urban areas, because everyone riding the subways is exposed to all those other pathogens. COVID-19 will be worse if you have a pre-existing infection, and it often kills by reducing your resistance to other pneumonia-causing pathogens.

  16. The sample size for this study wasn’t large enough.

    1. It is like you didnt pass any freshman year class in any subject you wander in to.

    2. Show your work.

  17. I had read the commentary in Science and the quote cited above knocked me out.
    The lead author of the Santa Clara study, Jay Bhattacharya, tells Science, “The argument that the test is not specific enough to detect real positives is deeply flawed.”
    What is deeply flawed is that statement. The ability to detect a “real” positive is sensitivity. And the degree to which a “true or real” positive is always positive in your test is one component of assay performance Specificity is when a subject known to be negative yields a positive test result. The questions around the study are not around sensitivity – false negatives- they are all around specificity – false positives. The assay data would generate a confidence interval for the specificity component of between 98% – 100%. Based on the lower bound, there is certainty that a test of that precision would yield 1.5% of samples testing positive when in fact they are not. And in fact they found 50 samples of 3300 were positive – 1.5%. How they arrived at their CI for the specificity component is important here. If the test performance is cleared up to everyones satisfaction then life goes on. If not, continue to develop a better test.

    1. Serological antibody studies are actually the only true way to prove exposure. PCR tests are more likely to show false results. I could explain this in detail because this is not something I just learned in a magazine. I’m a nurse. No one ever disputed serology studies- this is how we ensure someone actually has antibody. If the exposure was very recent, the antibodies would look different than weeks later and there is a lag time, but if anything you would get false NEGATIVES not positives. The PCR could go either way. You have to shed actual virus when it is replicating to get a positive PCR and often that PCR will remain positive if taken incorrectly, which is why you keep hearing about people being “reinfected.” It’s a false positive. I have never in my life seen anyone call serology bs. This is purely an attempt to convince you there cannot be heard immunity, you have not had this and you need to be locked up until you can be shot up with a vaccine. It’s all such a blatant lie and now everyone and their mother is an armchair scientist. It’s like they’ve forgotten there are people out there who already HAVE THEIR NUMBER.

    2. No 1.5% of the (50) positives would be false. What you are saying is 100% false positives.

  18. Sorry, I know it’s an appeal to authority, but I’m inclined to trust guys like Bhattacharya and Ioannidis over anyone from Columbia… Because NY sucks.

  19. With a 0.2% IFR, New York City’s 7,479 deaths (CDC data as of 4/22) imply total infections of 3,739,500 in the city.

    New York City has ~8.4 million people. Not quite half of them being infected actually sounds plausible to me. (If you assume 1 infected person arrived in NYC in mid-January, and the R0 is actually 3, that requires less than 14 generations, which could potentially have happened as fast as end of February. Now, obviously populations are finite, and the R starts dropping before you get near 50% infected, but lockdowns didn’t start until mid-March, and there was probably more than 1 infected person who arrived in NYC at various points, too.) That’s the thing about supposing R is super high, it spreads pretty fast, and then you have to look at how late those lockdowns were. (I’m willing to agree the 0.12 IFR is probably unreasonably low).

    And of course, a 0.2% IFR is an estimated average over some sort of age distribution – we don’t know if NYC’s age distribution is the same or not. What we really need is age-bracket specific IFRs, not some general IFR. If, for whatever reason, NYC averages 10 years older than the sample population, that makes a pretty big difference. (Or if NYC has a higher preponderance of comorbidities … our models should be more complicated at this point than ‘get one magic number and multiply’).

    If I’m going to fault the study for one thing, it’s making a single estimate of IFR, given the significant age skew.

    But rather than criticize their findings, they’ve presented a hypothesis on IFR that can definitely be tested. If they’re right, then literally half of NYC is infected, and that would swamp any of the claimed problems with specificity. Rather than attacking the authors, someone should arrange a random serological survey of new yorkers and see what the data says.

    1. One reason why NY’s covid-19 death rate is higher than expected:

      They’re basically promoting the spread of covid-19 among the people most vulnerable to the disease.

  20. Are we really gonna take the word of someone from Columbia U? Shouldn’t they get a real degree first?

  21. Two independent papers both suggesting that COVID-19 is more widely spread lends weight to the thesis. It doesn’t mean it’s correct, but it’s weighty. And people criticizing the studies is the normal process of science (although I note that one critic seemed pointed and personal in his attack).

    What’s happening here is a mostly unscientific media trying to report on science. So any suggestion of a story that the virus is not as bad as we thought gets trumpeted, and any suggestion that the trumpeting was wrong gets trumpeted even louder. But it’s the normal scientific process at work.

    Science is about replicability. Instead of immediately making up ones minds and staking out a hill to die on, we should instead by trying to replicate or fix the studies. That’s not going to happen overnight. But in the short term we can keep testing and keep collecting data. Admit that places like New York are going to be genuine outliers because of its unique demographics and situation.

    In the end though, I see two independent studies saying mostly the same thing. That adds up to more than nothing in my book.

    1. A Titer test is faaaaaaaaaarr more scientifically accurate than PCR. Sorry, those PCR tests are more likely to produce false positives than serology. This is an attempt for media to have you believe you didn’t have this and need a vaccine. End of story.

  22. So apparently Cuomo just gave preliminary results from an antibody study in NYC and… it’s 21%. Dropping the IFR even there to ~0.5%.

    1. I can’t fucking believe that people are still talking about contact tracing and isolation at this point. No fucking way you trace the contacts of over a million people in a crowded city. Contact tracing works when an outbreak is small and just getting started. This cannot be contained and it is stupid to try.

      1. I can’t fucking believe that people are still talking about contact tracing and isolation at this point.

        I said this when Ronnie was chatting up the test in Washington State that identified an asymptomatic HS kid retroactively and insisted they be cleared and ramp up production.

        Tractability then would’ve been plausible and would’ve made sense as the kid himself didn’t travel to China and, apparently, didn’t know anyone who tested positive. But, media being what it is/was, it was Trump’s fault the FDA didn’t approve this test on what was just as reasonably a false positive.

      2. Containment? It’s called herd immunity! It’s already occurring. No surprise at all here! There was no way you were EVER going to contain it and since the fatality rate is no more than a bad flu year, it’s time to get back to work!

    2. Got a link with decent reporting (hah) that includes details?

  23. Another problem critics allege specifically with the Santa Clara study is that the research participants were recruited via Facebook.

    So it was like journalists who take the “pulse of America” by scrolling through twitter posts.

    1. As if. Can you imagine how terrible the data would be if they recruited people in 280 characters or less?

  24. “As I noted earlier, given the number of deaths in New York City from COVID-19 such a relatively low IFR would implausibly suggest that essentially every resident of the Big Apple has already been infected by the virus.”
    Not implausible at all. But, first, my calculations using the Stanford study estimates 5.74M NYC resident out of 8,4M. My belief is that the virus got NYC way before anyone knew and was doing its thing well before the city took any actions. By the time they got going the horse was out of the barn.

    Can you really doubt that a city with 27,000 people per square mile and whose citizens virtually all use public transportation wold not have almost everyone exposed?

    1. Correct. I’m feeling like the false narratives continue on all fronts. Couldn’t possibly be so many people with this.. otherwise we’d be talking about herd immunity and you wouldn’t need your Bill Gates funded vaccine!!
      I’m so over this!!

  25. Ron, you need to update this article and add the New York study. With the positive antibody rate over 20% in NYC, the argument that false positives invalidate the data is getting pretty weak. None of the studies included a sampling of the entire community, but I have doubts that including children and nursing home residents would lower the infection rate.

    1. Children aren’t being tested. Testing children would likely bring the count up tremendously. For then this sounds like no more than your basic minor sniffle.

  26. I’m a nurse. When we Titer antibody for other viruses we don’t play this “false positives/false negatives” game. The values are taken at Face Value, if you will. This is the only disease I’ve ever heard of where we WANT to “believe” no one has had this. Not likely since the majority of people infected are in nursing homes and nursing homes are visited by family and have plenty of staff to carry it all in. Therefore, there are always “carriers” and as with most disease not all carriers know they have an illness not so they ever get sick (nothing new here). The other reality is that we can also talk about the false positives for the PCR that are just as possible, inflating the numbers who have had the disease, not to mention the most obvious factor: having Covid and dying with it is not dying OF it and the cat is out of the bag that this is being erroneously counted for higher hospital reimbursement.
    Know what I think? This has been everywhere. And now agencies who made false predictions based on faulty statistics (yeah, I can read those also and a crystal ball would have been just as accurate) and assisted the wealth transfer of the world to those who’ve had their sights on it, are attempting to backpedal in order to appear absolved or guilt. Don’t help them- you’re wrong also.

    1. *nor do they ever get sick
      *absolved of guilt

  27. I said this when Reason reported this study a few days ago. I’d really like to know why the Reason writers with their gigantic brains weren’t at least a little suspicious.

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