18 ms·

Hundreds of thousands in L.A. may have been infected with coronavirus: study

261 points by contemporary343 6y ago

joe_the_user 6y ago
Paywalled
- infecto 6y ago
  https://github.com/iamadamdev/bypass-paywalls-firefox https://github.com/iamadamdev/bypass-paywalls-firefox
- tzm 6y ago
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  - herman_toothrot 6y ago
    This used to work on some sites, but i just tried it here about 20 times and couldn't get it work.
eightysixfour 6y ago
Does this study make the same mistakes as the Standford study?
- benchtobedside 6y ago
  One particular criticism of the Stanford study was that they recruited via Facebook adverts, and that method may be influenced in recruitment by the "desire to get a test if you had reason to believe that you, or someone near you, had the virus" In more detail: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... This USC study seems to have recruited differently: "Participants were recruited via a proprietary database that is representative of the county population. The database is maintained by LRW Group, a market research firm" Via: http://www.publichealth.lacounty.gov/phcommon/public/media/mediapubhpdetail.cfm?prid=2328 http://www.publichealth.lacounty.gov/phcommon/public/media/m...
  - jupp0r 6y ago
    The flaw was that participation was voluntary, with the effects you describe. I think this is also the case with this study. I'm not sure how a non-voluntary study could be conducted, you can't really force people to participate in this. edit: typo
  - longtimegoogler 6y ago
    The biggest flaw is that they didn't use the confidence intervals associated with the specificity in their calculations properly. Given the CI's of the specificity all 50 positives could have been false positives so we can't conclude anything from the study.
- DangerousPie 6y ago
  Some of the authors are the same, so most likely yes.
JoeAltmaier 6y ago
Not sure what significance there is. Sure, some intermediate statistics change (e.g. what is the true percentage of bad reactions). But nothing changes the true death rate, which is what, the single largest mortality stat in America right now? Arguing over this fraction and that, isn't going to make this less deadly.
- StavrosK 6y ago
  It literally is, though. If the denominator is three times larger than we thought, that makes the virus three times less deadly.
  - Consultant32452 6y ago
    And of course the second most important thing to know I think is whether or not antibodies confer immunity. We've all been assuming herd immunity is the key, either by vaccine or the "we all get it, but slowly enough to not overrun the healthcare system" method. Right now we're on the edge of a precipice. My read of "the people" is they will hold off a bit longer if some reasonable-sounding fact-ish based plan comes out soon. It can be a little wrong, but it has to be credible. Knowing how many people have had it, and whether or not those people are now safe, is imo the two biggest components of planning the next steps. If we can't get credible answers to those questions soon, I believe the population will just start making decisions based on hunches/beliefs/feelings/etc. Some will remain isolated, others will rebel. It won't be pretty.
  - tunesmith 6y ago
    Keeping in mind though that if that means it's more contagious in turn, it also makes it that much harder to achieve herd immunity. Not that we should be considering "natural" herd immunity under any circumstances. It's a horrible idea.
    - whb07 6y ago
      No one ever said you wouldn't get this though. The whole idea from the get go was to prevent a run on the hospitals, not to prevent society from catching this. Every passing day more data and studies are reflecting the realities of this disease not being as deadly as imagined. So perhaps, just like chickenpox, its better to just get it as a kid then to face it later as an adult.
papeda 6y ago
Here is a basic question: how are the sensitivity and specificity (false negative and false positive rates, IIRC) of these tests determined? It seems like a learning problem with noisy labels. Does anyone know what they do in practice? Especially chaotic situations like this where there aren't reference tests? Are there reference positive and negative samples? One concern also referenced for the Stanford study was that, as mentioned in a USC popular writeup on this study linked elsewhere on this post, > Premier Biotech, the manufacturer of the test that USC and L.A. County are using, tested blood from COVID-19-positive patients with a 90 to 95% accuracy rate. They must be factoring this into the 2-5% infection rate number somewhere?
- deleted 6y ago
  [deleted]
- makomk 6y ago
  Reference negative samples are relatively easy, at least in theory. Any blood samples drawn before the Covid-19 outbreak started are guaranteed to be 100% negative.
- jupp0r 6y ago
  In the Stanford study, they used blood samples that were taken before the epidemic to determine the true/false negative rate, and blood from patients that tested PCR positive in the past to determine true/false positive rate.
  - loser777 6y ago
    ...which has been characterized as being analyzed in a highly suspect way [1], where only point estimates of the specificity were used. [1] https://news.ycombinator.com/item?id=22924118 https://news.ycombinator.com/item?id=22924118
  - longtimegoogler 6y ago
    The Stanford study didn't properly include the specificity in their predictions. See here, https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...
bla3 6y ago
NYC has 20x the deaths / 100k people, so under the assumption that number of deaths are on comparable trajectories (due to both locations being under lockdown, maybe not as unrealistic as a few weeks ago), NYC's prevalence could be 56%-112%. This could be one explanation for why numbers are going down in NYC, or the 112% being larger than 100% could suggest that either the situations aren't comparable or that the LA study's numbers are a bit high.
- deleted 6y ago
  [deleted]
- lm28469 6y ago
  You can't just take numbers and multiply them like that. What about average age? Number of icu beds? Effect of temperature/humidity on the virus? Population density? &c. There are so many variables
  - zucker42 6y ago
    The point is that either these numbers are not accurate, or that there are crucial differences between LA and NYC. Either conclusion is interesting.
- hilbertseries 6y ago
  I don’t really understand your point. The error bars would be calculated differently for a larger sample. If you had 100/100 positives with a five percent error you wouldn’t say the true amount is 95 to 105. You’ve done some sloppy statistics and claimed this invalidates the work...
- TheBlight 6y ago
  LA's numbers seemingly agree with Santa Clara's numbers as well. I would guess NYC probably has a much higher rate of infection (possibly due to http://web.mit.edu/jeffrey/harris/HarrisJE_WP2_COVID19_NYC_13-Apr-2020.pdf http://web.mit.edu/jeffrey/harris/HarrisJE_WP2_COVID19_NYC_1... ?) But 50%+ seems pretty high. Is it also possible different strains are dominant in California and NYC with different mortality characteristics? There is also the issue of weather. A recently leaked DHS report indicates sunlight radically reduces virus half-life and it's also affected by temperature and humidity. Maybe subway + weather + (possibly) strain of differing virulence can explain the discrepancy?
strangeloops85 6y ago
Some more information about the study here: https://pressroom.usc.edu/what-a-usc-la-county-antibody-study-can-teach-us-about-covid-19/ https://pressroom.usc.edu/what-a-usc-la-county-antibody-stud... Population is supposed to be representative of LA county. Tests are from Premier Biotech with some preliminary data on false negative/ false positive rates shown. I suspect assumptions related to the test itself, rather than population, may be a bigger factor for any inaccuracies. There's also the question of whether antibody response implies immunity for SARS-COV2 Another interesting aspect of the result was 6% of men showed antibodies but only 2% of women tested. Also: --2.4% of people between the ages of 18 and 34 had antibodies to the coronavirus --5.6% of people between 35 and 54 had antibodies --4.3% of between 55 and older had antibodies Edit: The key assumption that really, really needs to be triply checked here is the specificity of the test. They're assuming 99.5%, similar to the Stanford study I believe. If it's closer to 98% then prevalence estimate confidence intervals should include 0%, I believe. Also should be noted that the same PI on the Stanford study, Jay Bhattacharya, is also involved in this. Same criticisms likely apply here - more caution needed! Second edit: On further reflection, I think these studies could do serious damage based on how the results are being announced by press-release - in this case, afaik there's no pre-print. In our current environment this isn't just science. Policy is being enacted and people may die because of poorly framing results. Everyone involved needs to take a step back and think through this carefully. Also - did anyone figure out why a hedge fund guy was an author on the Stanford pre-print? And why that same guy then published a Wall Street Journal op-ed about the study without identifying himself as a co-author? Shady stuff.
- tempsy 6y ago
  I’m very skeptical. Why were they so few hospitalizations in LA vs NYC if such a large % in LA contracted Covid? Is this suggesting that a much, much higher % in NYC have it (and the number of those with any serious symptom and thus need for hospitalization was higher)?
  - teilo 6y ago
    Yes, that is the implication. And if this is the case, that is very good news.
TheBlight 6y ago
Makes it a bit harder to deny the validity of the Stanford/Santa Clara results. They're virtually the same.
- Barrin92 6y ago
  also in line with the dutch results a week ago (https://www.nytimes.com/reuters/2020/04/16/world/europe/16reuters-health-coronavirus-netherlands-study.html https://www.nytimes.com/reuters/2020/04/16/world/europe/16re...)
- lalaland1125 6y ago
  One issue is that the study design and probably analysis is very similar to the Santa Clara study (they are using the same test kits and have shared coauthors on both studies). It's not really independent replication when both are potentially using flawed kits and analysis.
- tunesmith 6y ago
  Looking forward to what the science heads on my twitter feed say about it. They were positively withering in their criticism regarding the Santa Clara study.
- tempsy 6y ago
  How do you explain the low number of hospitalizations and deaths in LA vs NYC? If these numbers hold then you’d expect NYC to be close to herd immunity given the difference in fatalities.
  - TheBlight 6y ago
    See: https://news.ycombinator.com/item?id=22928754 https://news.ycombinator.com/item?id=22928754
    - tempsy 6y ago
      More questions than answers. It hasn’t been hot in LA so suggesting it has to do with heat doesn’t make sense imo.
mikekij 6y ago
Tl;dr: It looks like ~4.2% of Los Angeles residents may have already been affected. Current stats from [https://covid-19.direct/county/CA/Los%20Angeles https://covid-19.direct/county/CA/Los%20Angeles]: Confirmed cases: 12,349 Deaths: 601 Population: 4M Implied fatality rate: 4.87% If this study is correct (~4.2% prevalence): Cases: 167,580 Deaths: 601 Implied fatality rate: 0.36% There is massive difference between the appropriate response to an illness with a 5% fatality rate and an illness with a 0.36% fatality rate.
- TheBlight 6y ago
  I think your math is a bit off. From the paper 221,000 to 442,000 adults are believed to be infected. This makes the IFR ~0.13-0.27%. Source: http://www.publichealth.lacounty.gov/phcommon/public/media/mediapubhpdetail.cfm?prid=2328 http://www.publichealth.lacounty.gov/phcommon/public/media/m...
- babesh 6y ago
  You need to factor in that some of the currently infected are going to die.
- RobAtticus 6y ago
  Certainly, but I don't think anyone was assuming 5% fatality rate. There were concerns about it being 1-3% fatality, but even those would be worst cases. Worth noting that .36 is roughly 3x as deadly as the flu.
  - artursapek 6y ago
    3x as deadly as the flu, in a population of people who have already been exposed to the flu (and some even taking flu vaccines constantly). The evidence will continue to build that this virus is pretty benign compared to all of the fear mongering has been suggesting. Of course, HN downvoted me when I suggested this last time https://news.ycombinator.com/item?id=22685457 https://news.ycombinator.com/item?id=22685457
    - tunesmith 6y ago
lalaland1125 6y ago
Understanding this study is very difficult because they haven't released all of the details about statistical procedures, recruitment, raw data, etc, but I would be worried that this study will have similar issues to the recently published Santa Clara study (both use the same lab test and share several authors). I highly recommend that people read https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... for information about for information on how the Santa Clara study messed up. TLDR: Incorrect statistics, incorrect analysis, and incorrect sampling probably led to a vast overestimate of both prevalence and certainty in that high prevalence estimate.
- tempsy 6y ago
  The huge difference is that the LA one claims to have tested a random sample of people while the Stanford one did not.
  - tunesmith 6y ago
    Doesn't sound like that is a sufficient difference, however, if they also screwed up the stats and the analysis.
  - eightysixfour 6y ago
    Some of the same authors, possible/likely they are using the same test.
  - longtimegoogler 6y ago
    That isn't huge. The biggest issue with the Stanford study was that they didn't take into account the Confidence Intervals of the Specificity.
jedberg 6y ago
What impact will this, or should it, have on public policy?
- TheBlight 6y ago
  In isolation I don't think this study can really shift the differing and primarily political response momentums the various states have going. Truly randomized nation-wide studies would need to be completed probably by the CDC for there to be wide-spread consensus on the results. The politics are going to move quicker than the science.
baron816 6y ago
Is it possible that there’s a “West Coast/Asian strain” that’s a lot less serious than the “East Coast/European strain”?
- TheBlight 6y ago
  As more serology surveys are completed I expect this question to come to the forefront.
  - DangerousPie 6y ago
    How exactly? Serology has nothing to do with figuring out which version of the virus you have, ignoring the fact that there are no distinct "strains" to begin with.
    - TheBlight 6y ago
      I suspect we're going to see different IFRs in NYC vs. the West Coast. There are already at least 2 strains: https://www.forbes.com/sites/lisettevoytko/2020/03/04/discovery-of-2-strains-of-covid-19-coronavirus-hints-at-how-it-evolved/#6fd538037094 https://www.forbes.com/sites/lisettevoytko/2020/03/04/discov...
- kens 6y ago
  There's been a bunch of genomic analysis. Yes, the West coast strains are closer to Asian and the East coast strains are closer to European. But the differences between strains are believed to not have an effect on the disease. https://nextstrain.org/narratives/ncov/sit-rep/en/2020-04-17 https://nextstrain.org/narratives/ncov/sit-rep/en/2020-04-17 https://nextstrain.org/help/coronavirus/FAQ#is-one-strain-of-the-covid-19-virus-more-severe https://nextstrain.org/help/coronavirus/FAQ#is-one-strain-of...
icodestuff 6y ago
Does anyone have a link to the actual study? LA Times link doesn't include it. Other than the selection criteria for participants, it doesn't sound from the pressroom.usc.edu link that it's any better than the Santa Clara study, and perhaps worse, given the smaller number of participants. The pressroom link mentions an "accuracy" number, but not specificity and sensitivity.
- DangerousPie 6y ago
  That really tells you everything you need to know about this study already, doesn't it? If they put out the press release before the actual study you know what the authors' priorities are.
- strangeloops85 6y ago
  Just a press release, no pre-print. That being said it was being co-run by LADPH it seems. Many people involved were also involved with the Stanford study which has been very thoroughly criticized for its assumptions.
throwaway122378 6y ago
863 people were in this study. A market data firm selected those people. LA proper has about 16,000,000 people. This study should be taken with a grain of salt either way for now.
- HideousKojima 6y ago
  Provided the people were chosen truly randomly/make up a representative sample of the population, 863 is more than enough to get an accurate estimate of the infection rate. ~1000 is a big enough sample size for the entire US, let alone just Los Angeles
  - qqqwerty 6y ago
    I used to work on survey designs in my old job. I am having a hard time coming up with a way that they could possibly control for selection bias. We are in the middle of a pandemic, the people willing to risk leaving their homes to get tested is going to be highly skewed towards individuals that believe they have already had the infection. It's possible that they asked the participants about this, and adjusted their weights accordingly, but considering that this study shares authors with the Santa Clara study, and that study did not control for selection bias, I have my doubts.
  - throwaway122378 6y ago
    Where's the marketing company's criteria for sample selection? How are the communicating and choosing the people? Are they all within the same locality? And no 863 is not representative of LA. LA is made up of individual communities and some never leave those communities. Some communities are pass through for commuters. Really important where those 863 are from. All are 863 from a small area? Are some from Pasadena and other from Santa Monica. What about Covina or Redondo? LA or Beverly Hills.
bestnameever 6y ago
They appear to be using an antibody test from Premier Biotech. However, I can't gain clarity on whether we know if these tests are even accurate or reliable. "But some COVID-19 antibody tests, including those being used by public health departments in Denver and Los Angeles and provided to urgent care centers in Maryland and North Carolina, were supplied by Chinese manufacturers that are not approved by China's Center for Medical Device Evaluation, a unit of the National Medical Product Administration, or NMPA, the country's equivalent of the U.S. Food and Drug Administration, NBC News has found. Two U.S. companies — Premier Biotech of Minneapolis and Aytu Bioscience of Colorado — have been distributing the tests from unapproved Chinese manufacturers, according to health officials, FDA filings and a spokesman for one of the Chinese manufacturers. Many of the unapproved tests appear to have been shipped to the U.S. after the FDA relaxed its guidelines for tests in mid-March and before the Chinese government banned their export just over two weeks later. If COVID-19 antibody tests are unreliable, they can produce false results, either negative or positive, health officials said. The use of such tests has been widely discussed as a way to ensure that employees are healthy enough to go back to work and to find COVID-19 survivors who may be able to provide blood plasma to severely ill patients. Officials at the Association of Public Health Laboratories have expressed concern about the reliability of the numerous antibody tests being sold or used across the country with little scrutiny. " see: https://www.nbcnews.com/health/health-news/unapproved-chinese-coronavirus-antibody-tests-being-used-least-2-states-n1185131 https://www.nbcnews.com/health/health-news/unapproved-chines...
- deleted 6y ago
  [deleted]
neonate 6y ago
https://archive.md/Whas8 https://archive.md/Whas8
korethr 6y ago
There's a logical jump from the 2nd to 3rd paragraph that bugs me, but upon reflection, I don't know if my objection is valid: > The initial results from the first large-scale study tracking the spread of the coronavirus in the county found that 2.8% to 5.6% of adults have antibodies to the virus in their blood, an indication of past exposure. > That translates to roughly 221,000 to 442,000 adults who have recovered from an infection, according to the researchers conducting the study, even though the county had reported fewer than 8,000 cases at that time. So, in the 2nd paragraph, there, a match for SARS-COV2 antibodies means an exposure. In the 3rd, it means an infection. I have always understood that exposure != infection. Yes, the former is a necessary precondition to the latter, but an exposure doesn't automatically and unconditionally become an infection. But then it occurred to me that the body probably isn't going to be generating antibodies unless a pathogen got past the body's initial lines of defense and required a more active response from the immune system. In which case then, perhaps it would be accurate to say antibodies == infection. Are we speaking then of asymptomatic carriers or those who never experienced more than mild symptoms and might not have realized they were infected? Am I splitting hairs here? Is this simply shorthand for "exposure that subsequently became an infection?", much in the same way I might freely use "LDAP Server", "Name Server", "Domain Controller" "Auth Server", to all refer to the same system in an on-prem Windows environment? Or, am I rightly objecting to unclear language that would lead to incorrect conclusions?
mlwiese 6y ago
This LA study has one of the same authors as the Stanford study (Neeraj Sood). It uses the same test and so it has the same issues with the false positive rate. An honest person would address those but I didn't see that in the press release. This post describes the issues: https://medium.com/@balajis/peer-review-of-covid-19-antibody-seroprevalence-in-santa-clara-county-california-1f6382258c25 https://medium.com/@balajis/peer-review-of-covid-19-antibody... See also this thread: https://news.ycombinator.com/item?id=22924118 https://news.ycombinator.com/item?id=22924118
sjg007 6y ago
Both the LA and Stanford studies are junk. Easily explained by false positives inherent to the test. Stuff like this is why pre-print services can have disastrous consequences. https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...
- microdrum 6y ago
  So, in your ideal world, we would never do serosurveys for surveillance of low incidence diseases, right? Any Type 1 error is too much Type 1 error, right? I'm sorry that literally all of the seroprevalence data hurt your priors. But the virus is widespread, not very deadly, and people are going to go back to work soon. You can stay home. You will be safe at home.
  - VyperCard 6y ago
    No need to be condescending. This is hacker news not Reddit.
- DeonPenny 6y ago
  That article is junk. Even the fact that it quotes Santa Claras deaths at 100 deaths is wrong because it was only 70 at the time. This entire blog is rife with mathematical and statistical errors.
gok 6y ago
I see a lot of pushback on these studies showing high infection rates. To those people, what rate do you actually believe and why?
- skybrian 6y ago
  Based on these studies I think >90% of people in California don't have it, and how much higher is unknown.
- zucker42 6y ago
  There's not enough data to "believe" anything, and most of the pushback is because the studies are methodologically flawed. I think that fatality rate estimates between 0.5% and 1% seem to best match some of the early data on isolated populations, but I'm far from an epidemiological expert. That said, I think people would be a lot more accepting of data contradicting those rates if it didn't have clear issues.
- mcnamaratw 6y ago
  I feel more informed when I see an infection rate that's substantially higher than the rate of false positives from the test. So the NYC test of pregnant women at (13? 15%?) seems to be much higher than the 1% to 4% range of false positives that people seem to be estimating. But when test results are "down in the noise" I don't feel we're necessarily measuring anything.
- robryan 6y ago
  I don’t see our squares with our Australian numbers. How have we been able to bring the case numbers right down if there are as many asymptomatic cases and as high an R0 as these studies suggest. Our overall testing of people with symptoms has an under 2% positive rate with one of the highest per capita testing rates in the world. We have a lockdown but it isn’t so extreme as to be able to stop the kind of spread these studies are suggesting. The vast majority of our non imported cases have also been successfully contact traced, people by and large seem to be contracting it from other confirmed cases.
natrik 6y ago
https://covid19tracker.health.ny.gov/views/NYS-COVID19-Tracker/NYSDOHCOVID-19Tracker-Fatalities?%3Aembed=yes&%3Atoolbar=no&%3Atabs=n https://covid19tracker.health.ny.gov/views/NYS-COVID19-Track... 89% of total fatalities in New York have at least 1 comorbidity. I wonder to what extent anyone with unknown cause of death or death due to cancer, but also had COVID-19 gets lumped into the death due to COVID-19 category.
- fsh 6y ago
  The overall mortality rate in NYC is more than double the usual [1]. I guess that most people above a certain age have at least one comorbidity such as diabetes or high blood pressure. [1] https://www.nytimes.com/interactive/2020/04/10/upshot/coronavirus-deaths-new-york-city.html https://www.nytimes.com/interactive/2020/04/10/upshot/corona...
rdtsc 6y ago
3.4% mortality rate reported by WHO seems to be not as accurate then https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---3-march-2020 https://www.who.int/dg/speeches/detail/who-director-general-... --- Globally, about 3.4% of reported COVID-19 cases have died --- That was used as a basis quite a few decisions, how to treat patients, when to close / open various locations, etc. It does say "reported" in the report, but I think often that part of ignored and many officials assumed it to be as a rate based on infected cases. The article does mention this issue, and I wonder what the new / updated mortality rate is then based on this data.
- zucker42 6y ago
  I think all the serious scientific papers I've read have long put fatality estimates far below what early WHO press releases suggested.
- jsnell 6y ago
  I mean, you're tecnically correct in that the number is no longer accurate. But actually the change has been in the other direction. That link is talking about the CFR, not the IFR, and the CFR is up to 7% these days. (170k dead out of 2.5M confirmed cases). No credible source that I saw ever suggested that the IFR was 3%, and that is not what any decisions were based on. Everyone knows that some cases will be missed. The early IFR estimates were all huge ranges like 0.1%-2%, precisely since there was so little information early on about how many cases were not being detected. (And it is surprising how little we've managed to narrow that range down). There are other claims in that WHO link that are obviously wrong in retrospect. E.g. the claim that Covid transmits less efficiently than the flu.
Smoosh 6y ago
Interesting that this article says only 2~3% with antibodies globally. I'm left wondering how reliable the testing (of all kinds) is. https://www.theguardian.com/society/2020/apr/20/studies-suggest-very-few-have-had-covid-19-without-symptoms https://www.theguardian.com/society/2020/apr/20/studies-sugg...
longtimegoogler 6y ago
The Stanford study in Santa Clara that used Premier Biotech appears to be very misleading. Given the confidence intervals on the specificity all 50 positive cases out of the 3330 tested could just be false positives. See Gelman's article on the topic. https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... I am similarly skeptical of the findings here.
- Rury 6y ago
  Especially considering the test used here was also, Premier Biotech's. Their manual [1] states, that other coronavirus strains can lead to false positives in the test: >Positive results may be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E [1]https://imgcdn.mckesson.com/CumulusWeb/Click_and_learn/Premier_Biotech_COVID19_Package_Insert.pdf https://imgcdn.mckesson.com/CumulusWeb/Click_and_learn/Premi...
deleted 6y ago
[deleted]
vanniv 6y ago
With the NYC analysis here, everyone is missing one unknowable piece of information. We know that the initial major outbreak in NYC was with a strain from Europe, while the initial major outbreak in California was with an Asia-origin strain. These might be differently dangerous. If the NYC/Europe strain is just 20%-30% more fatal than the Asian one, the maths all start being believable (you start saying that 30-45% of NYC has been infected -- which, unlike 60-100+%, is quite believable. It seems likely that some vulnerable neighborhoods in NY have effectively everyone infected, but that is probably not universally true. It also seems quite believable that we are nearing the point where the majority of folks in NYC have been exposed. If nothing else, the subway is still seeing quite active use, and must be a breeding ground for infection -- and yet, hospitalization has started declining, meaning that new infections are slowing down -- meaning that at least among folks that still go out and about, there must just be fewer people to infect. With subway use still being as high as it is, it seems like it must be true that, amongst the population using it, R could only fall below 1 if herd immunity (in the rider population) was beginning to form. This also jives with the numbers we are seeing, where reported cases are down despite both increased testing and looser counting.
shadowprofile77 6y ago
This recent Swedish study was done in (what seems) to be a way that's much less prone to bias than soliciting people via Facebook posts. It was also based on tests collected from blood donor samples, so none of the specific bias of the Stanford study (which to me also seems like a huge flaw even if other sources of evidence are pointing to similar IFR numbers and undercounting) In any case, the Swedish findings cited for Stockholm in the analysis linked to in this COVID19 subreddit post indicate a similarly low overall IFR of far below 1%. It is worth noting that blood donors would probable tend more towards youth and general good health, which could skew its demographic profile. Also, depending on donors' motives for donating (maybe they thought it would include a COVID test) could skew results in different and unpredictable ways. https://www.reddit.com/r/COVID19/comments/g4znbg/at_least_11_of_tested_blood_donors_in_stockholm/ https://www.reddit.com/r/COVID19/comments/g4znbg/at_least_11...
biolurker1 6y ago
If that's a testing mistake and gives rise to political pressure, it's a disaster
pcdoodle 6y ago
May have been? Quick it with the pandemic porn.

joe_the_user 6y ago

Paywalled

infecto 6y ago
https://github.com/iamadamdev/bypass-paywalls-firefox https://github.com/iamadamdev/bypass-paywalls-firefox
tzm 6y ago
Press `esc` key prior to page load completion
- herman_toothrot 6y ago
  This used to work on some sites, but i just tried it here about 20 times and couldn't get it work.

eightysixfour 6y ago

Does this study make the same mistakes as the Standford study?

benchtobedside 6y ago
One particular criticism of the Stanford study was that they recruited via Facebook adverts, and that method may be influenced in recruitment by the "desire to get a test if you had reason to believe that you, or someone near you, had the virus" In more detail: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... This USC study seems to have recruited differently: "Participants were recruited via a proprietary database that is representative of the county population. The database is maintained by LRW Group, a market research firm" Via: http://www.publichealth.lacounty.gov/phcommon/public/media/mediapubhpdetail.cfm?prid=2328 http://www.publichealth.lacounty.gov/phcommon/public/media/m...
- jupp0r 6y ago
  The flaw was that participation was voluntary, with the effects you describe. I think this is also the case with this study. I'm not sure how a non-voluntary study could be conducted, you can't really force people to participate in this. edit: typo
- longtimegoogler 6y ago
  The biggest flaw is that they didn't use the confidence intervals associated with the specificity in their calculations properly. Given the CI's of the specificity all 50 positives could have been false positives so we can't conclude anything from the study.
DangerousPie 6y ago
Some of the authors are the same, so most likely yes.

JoeAltmaier 6y ago

Not sure what significance there is. Sure, some intermediate statistics change (e.g. what is the true percentage of bad reactions). But nothing changes the true death rate, which is what, the single largest mortality stat in America right now? Arguing over this fraction and that, isn't going to make this less deadly.

StavrosK 6y ago
It literally is, though. If the denominator is three times larger than we thought, that makes the virus three times less deadly.
- Consultant32452 6y ago
  And of course the second most important thing to know I think is whether or not antibodies confer immunity. We've all been assuming herd immunity is the key, either by vaccine or the "we all get it, but slowly enough to not overrun the healthcare system" method. Right now we're on the edge of a precipice. My read of "the people" is they will hold off a bit longer if some reasonable-sounding fact-ish based plan comes out soon. It can be a little wrong, but it has to be credible. Knowing how many people have had it, and whether or not those people are now safe, is imo the two biggest components of planning the next steps. If we can't get credible answers to those questions soon, I believe the population will just start making decisions based on hunches/beliefs/feelings/etc. Some will remain isolated, others will rebel. It won't be pretty.
- tunesmith 6y ago
  Keeping in mind though that if that means it's more contagious in turn, it also makes it that much harder to achieve herd immunity. Not that we should be considering "natural" herd immunity under any circumstances. It's a horrible idea.
  - whb07 6y ago
    No one ever said you wouldn't get this though. The whole idea from the get go was to prevent a run on the hospitals, not to prevent society from catching this. Every passing day more data and studies are reflecting the realities of this disease not being as deadly as imagined. So perhaps, just like chickenpox, its better to just get it as a kid then to face it later as an adult.

papeda 6y ago

Here is a basic question: how are the sensitivity and specificity (false negative and false positive rates, IIRC) of these tests determined? It seems like a learning problem with noisy labels. Does anyone know what they do in practice? Especially chaotic situations like this where there aren't reference tests? Are there reference positive and negative samples? One concern also referenced for the Stanford study was that, as mentioned in a USC popular writeup on this study linked elsewhere on this post, > Premier Biotech, the manufacturer of the test that USC and L.A. County are using, tested blood from COVID-19-positive patients with a 90 to 95% accuracy rate. They must be factoring this into the 2-5% infection rate number somewhere?

deleted 6y ago
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makomk 6y ago
Reference negative samples are relatively easy, at least in theory. Any blood samples drawn before the Covid-19 outbreak started are guaranteed to be 100% negative.
jupp0r 6y ago
In the Stanford study, they used blood samples that were taken before the epidemic to determine the true/false negative rate, and blood from patients that tested PCR positive in the past to determine true/false positive rate.
- loser777 6y ago
  ...which has been characterized as being analyzed in a highly suspect way [1], where only point estimates of the specificity were used. [1] https://news.ycombinator.com/item?id=22924118 https://news.ycombinator.com/item?id=22924118
- longtimegoogler 6y ago
  The Stanford study didn't properly include the specificity in their predictions. See here, https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...

bla3 6y ago

NYC has 20x the deaths / 100k people, so under the assumption that number of deaths are on comparable trajectories (due to both locations being under lockdown, maybe not as unrealistic as a few weeks ago), NYC's prevalence could be 56%-112%. This could be one explanation for why numbers are going down in NYC, or the 112% being larger than 100% could suggest that either the situations aren't comparable or that the LA study's numbers are a bit high.

deleted 6y ago
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lm28469 6y ago
You can't just take numbers and multiply them like that. What about average age? Number of icu beds? Effect of temperature/humidity on the virus? Population density? &c. There are so many variables
- zucker42 6y ago
  The point is that either these numbers are not accurate, or that there are crucial differences between LA and NYC. Either conclusion is interesting.
hilbertseries 6y ago
I don’t really understand your point. The error bars would be calculated differently for a larger sample. If you had 100/100 positives with a five percent error you wouldn’t say the true amount is 95 to 105. You’ve done some sloppy statistics and claimed this invalidates the work...
TheBlight 6y ago
LA's numbers seemingly agree with Santa Clara's numbers as well. I would guess NYC probably has a much higher rate of infection (possibly due to http://web.mit.edu/jeffrey/harris/HarrisJE_WP2_COVID19_NYC_13-Apr-2020.pdf http://web.mit.edu/jeffrey/harris/HarrisJE_WP2_COVID19_NYC_1... ?) But 50%+ seems pretty high. Is it also possible different strains are dominant in California and NYC with different mortality characteristics? There is also the issue of weather. A recently leaked DHS report indicates sunlight radically reduces virus half-life and it's also affected by temperature and humidity. Maybe subway + weather + (possibly) strain of differing virulence can explain the discrepancy?

strangeloops85 6y ago

Some more information about the study here: https://pressroom.usc.edu/what-a-usc-la-county-antibody-study-can-teach-us-about-covid-19/ https://pressroom.usc.edu/what-a-usc-la-county-antibody-stud... Population is supposed to be representative of LA county. Tests are from Premier Biotech with some preliminary data on false negative/ false positive rates shown. I suspect assumptions related to the test itself, rather than population, may be a bigger factor for any inaccuracies. There's also the question of whether antibody response implies immunity for SARS-COV2 Another interesting aspect of the result was 6% of men showed antibodies but only 2% of women tested. Also: --2.4% of people between the ages of 18 and 34 had antibodies to the coronavirus --5.6% of people between 35 and 54 had antibodies --4.3% of between 55 and older had antibodies Edit: The key assumption that really, really needs to be triply checked here is the specificity of the test. They're assuming 99.5%, similar to the Stanford study I believe. If it's closer to 98% then prevalence estimate confidence intervals should include 0%, I believe. Also should be noted that the same PI on the Stanford study, Jay Bhattacharya, is also involved in this. Same criticisms likely apply here - more caution needed! Second edit: On further reflection, I think these studies could do serious damage based on how the results are being announced by press-release - in this case, afaik there's no pre-print. In our current environment this isn't just science. Policy is being enacted and people may die because of poorly framing results. Everyone involved needs to take a step back and think through this carefully. Also - did anyone figure out why a hedge fund guy was an author on the Stanford pre-print? And why that same guy then published a Wall Street Journal op-ed about the study without identifying himself as a co-author? Shady stuff.

tempsy 6y ago
I’m very skeptical. Why were they so few hospitalizations in LA vs NYC if such a large % in LA contracted Covid? Is this suggesting that a much, much higher % in NYC have it (and the number of those with any serious symptom and thus need for hospitalization was higher)?
- teilo 6y ago
  Yes, that is the implication. And if this is the case, that is very good news.

TheBlight 6y ago

Makes it a bit harder to deny the validity of the Stanford/Santa Clara results. They're virtually the same.

Barrin92 6y ago
also in line with the dutch results a week ago (https://www.nytimes.com/reuters/2020/04/16/world/europe/16reuters-health-coronavirus-netherlands-study.html https://www.nytimes.com/reuters/2020/04/16/world/europe/16re...)
lalaland1125 6y ago
One issue is that the study design and probably analysis is very similar to the Santa Clara study (they are using the same test kits and have shared coauthors on both studies). It's not really independent replication when both are potentially using flawed kits and analysis.
tunesmith 6y ago
Looking forward to what the science heads on my twitter feed say about it. They were positively withering in their criticism regarding the Santa Clara study.
tempsy 6y ago
How do you explain the low number of hospitalizations and deaths in LA vs NYC? If these numbers hold then you’d expect NYC to be close to herd immunity given the difference in fatalities.
- TheBlight 6y ago
  See: https://news.ycombinator.com/item?id=22928754 https://news.ycombinator.com/item?id=22928754
  - tempsy 6y ago
    More questions than answers. It hasn’t been hot in LA so suggesting it has to do with heat doesn’t make sense imo.

mikekij 6y ago

Tl;dr: It looks like ~4.2% of Los Angeles residents may have already been affected. Current stats from [https://covid-19.direct/county/CA/Los%20Angeles https://covid-19.direct/county/CA/Los%20Angeles]: Confirmed cases: 12,349 Deaths: 601 Population: 4M Implied fatality rate: 4.87% If this study is correct (~4.2% prevalence): Cases: 167,580 Deaths: 601 Implied fatality rate: 0.36% There is massive difference between the appropriate response to an illness with a 5% fatality rate and an illness with a 0.36% fatality rate.

TheBlight 6y ago
I think your math is a bit off. From the paper 221,000 to 442,000 adults are believed to be infected. This makes the IFR ~0.13-0.27%. Source: http://www.publichealth.lacounty.gov/phcommon/public/media/mediapubhpdetail.cfm?prid=2328 http://www.publichealth.lacounty.gov/phcommon/public/media/m...
babesh 6y ago
You need to factor in that some of the currently infected are going to die.
RobAtticus 6y ago
Certainly, but I don't think anyone was assuming 5% fatality rate. There were concerns about it being 1-3% fatality, but even those would be worst cases. Worth noting that .36 is roughly 3x as deadly as the flu.
- artursapek 6y ago
  3x as deadly as the flu, in a population of people who have already been exposed to the flu (and some even taking flu vaccines constantly). The evidence will continue to build that this virus is pretty benign compared to all of the fear mongering has been suggesting. Of course, HN downvoted me when I suggested this last time https://news.ycombinator.com/item?id=22685457 https://news.ycombinator.com/item?id=22685457
  - tunesmith 6y ago

lalaland1125 6y ago

Understanding this study is very difficult because they haven't released all of the details about statistical procedures, recruitment, raw data, etc, but I would be worried that this study will have similar issues to the recently published Santa Clara study (both use the same lab test and share several authors). I highly recommend that people read https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... for information about for information on how the Santa Clara study messed up. TLDR: Incorrect statistics, incorrect analysis, and incorrect sampling probably led to a vast overestimate of both prevalence and certainty in that high prevalence estimate.

tempsy 6y ago
The huge difference is that the LA one claims to have tested a random sample of people while the Stanford one did not.
- tunesmith 6y ago
  Doesn't sound like that is a sufficient difference, however, if they also screwed up the stats and the analysis.
- eightysixfour 6y ago
  Some of the same authors, possible/likely they are using the same test.
- longtimegoogler 6y ago
  That isn't huge. The biggest issue with the Stanford study was that they didn't take into account the Confidence Intervals of the Specificity.

jedberg 6y ago

What impact will this, or should it, have on public policy?

TheBlight 6y ago
In isolation I don't think this study can really shift the differing and primarily political response momentums the various states have going. Truly randomized nation-wide studies would need to be completed probably by the CDC for there to be wide-spread consensus on the results. The politics are going to move quicker than the science.

baron816 6y ago

Is it possible that there’s a “West Coast/Asian strain” that’s a lot less serious than the “East Coast/European strain”?

TheBlight 6y ago
As more serology surveys are completed I expect this question to come to the forefront.
- DangerousPie 6y ago
  How exactly? Serology has nothing to do with figuring out which version of the virus you have, ignoring the fact that there are no distinct "strains" to begin with.
  - TheBlight 6y ago
    I suspect we're going to see different IFRs in NYC vs. the West Coast. There are already at least 2 strains: https://www.forbes.com/sites/lisettevoytko/2020/03/04/discovery-of-2-strains-of-covid-19-coronavirus-hints-at-how-it-evolved/#6fd538037094 https://www.forbes.com/sites/lisettevoytko/2020/03/04/discov...
kens 6y ago
There's been a bunch of genomic analysis. Yes, the West coast strains are closer to Asian and the East coast strains are closer to European. But the differences between strains are believed to not have an effect on the disease. https://nextstrain.org/narratives/ncov/sit-rep/en/2020-04-17 https://nextstrain.org/narratives/ncov/sit-rep/en/2020-04-17 https://nextstrain.org/help/coronavirus/FAQ#is-one-strain-of-the-covid-19-virus-more-severe https://nextstrain.org/help/coronavirus/FAQ#is-one-strain-of...

icodestuff 6y ago

Does anyone have a link to the actual study? LA Times link doesn't include it. Other than the selection criteria for participants, it doesn't sound from the pressroom.usc.edu link that it's any better than the Santa Clara study, and perhaps worse, given the smaller number of participants. The pressroom link mentions an "accuracy" number, but not specificity and sensitivity.

DangerousPie 6y ago
That really tells you everything you need to know about this study already, doesn't it? If they put out the press release before the actual study you know what the authors' priorities are.
strangeloops85 6y ago
Just a press release, no pre-print. That being said it was being co-run by LADPH it seems. Many people involved were also involved with the Stanford study which has been very thoroughly criticized for its assumptions.

throwaway122378 6y ago

863 people were in this study. A market data firm selected those people. LA proper has about 16,000,000 people. This study should be taken with a grain of salt either way for now.

HideousKojima 6y ago
Provided the people were chosen truly randomly/make up a representative sample of the population, 863 is more than enough to get an accurate estimate of the infection rate. ~1000 is a big enough sample size for the entire US, let alone just Los Angeles
- qqqwerty 6y ago
  I used to work on survey designs in my old job. I am having a hard time coming up with a way that they could possibly control for selection bias. We are in the middle of a pandemic, the people willing to risk leaving their homes to get tested is going to be highly skewed towards individuals that believe they have already had the infection. It's possible that they asked the participants about this, and adjusted their weights accordingly, but considering that this study shares authors with the Santa Clara study, and that study did not control for selection bias, I have my doubts.
- throwaway122378 6y ago
  Where's the marketing company's criteria for sample selection? How are the communicating and choosing the people? Are they all within the same locality? And no 863 is not representative of LA. LA is made up of individual communities and some never leave those communities. Some communities are pass through for commuters. Really important where those 863 are from. All are 863 from a small area? Are some from Pasadena and other from Santa Monica. What about Covina or Redondo? LA or Beverly Hills.

bestnameever 6y ago

They appear to be using an antibody test from Premier Biotech. However, I can't gain clarity on whether we know if these tests are even accurate or reliable. "But some COVID-19 antibody tests, including those being used by public health departments in Denver and Los Angeles and provided to urgent care centers in Maryland and North Carolina, were supplied by Chinese manufacturers that are not approved by China's Center for Medical Device Evaluation, a unit of the National Medical Product Administration, or NMPA, the country's equivalent of the U.S. Food and Drug Administration, NBC News has found. Two U.S. companies — Premier Biotech of Minneapolis and Aytu Bioscience of Colorado — have been distributing the tests from unapproved Chinese manufacturers, according to health officials, FDA filings and a spokesman for one of the Chinese manufacturers. Many of the unapproved tests appear to have been shipped to the U.S. after the FDA relaxed its guidelines for tests in mid-March and before the Chinese government banned their export just over two weeks later. If COVID-19 antibody tests are unreliable, they can produce false results, either negative or positive, health officials said. The use of such tests has been widely discussed as a way to ensure that employees are healthy enough to go back to work and to find COVID-19 survivors who may be able to provide blood plasma to severely ill patients. Officials at the Association of Public Health Laboratories have expressed concern about the reliability of the numerous antibody tests being sold or used across the country with little scrutiny. " see: https://www.nbcnews.com/health/health-news/unapproved-chinese-coronavirus-antibody-tests-being-used-least-2-states-n1185131 https://www.nbcnews.com/health/health-news/unapproved-chines...

deleted 6y ago
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neonate 6y ago

https://archive.md/Whas8 https://archive.md/Whas8

korethr 6y ago

There's a logical jump from the 2nd to 3rd paragraph that bugs me, but upon reflection, I don't know if my objection is valid: > The initial results from the first large-scale study tracking the spread of the coronavirus in the county found that 2.8% to 5.6% of adults have antibodies to the virus in their blood, an indication of past exposure. > That translates to roughly 221,000 to 442,000 adults who have recovered from an infection, according to the researchers conducting the study, even though the county had reported fewer than 8,000 cases at that time. So, in the 2nd paragraph, there, a match for SARS-COV2 antibodies means an exposure. In the 3rd, it means an infection. I have always understood that exposure != infection. Yes, the former is a necessary precondition to the latter, but an exposure doesn't automatically and unconditionally become an infection. But then it occurred to me that the body probably isn't going to be generating antibodies unless a pathogen got past the body's initial lines of defense and required a more active response from the immune system. In which case then, perhaps it would be accurate to say antibodies == infection. Are we speaking then of asymptomatic carriers or those who never experienced more than mild symptoms and might not have realized they were infected? Am I splitting hairs here? Is this simply shorthand for "exposure that subsequently became an infection?", much in the same way I might freely use "LDAP Server", "Name Server", "Domain Controller" "Auth Server", to all refer to the same system in an on-prem Windows environment? Or, am I rightly objecting to unclear language that would lead to incorrect conclusions?

mlwiese 6y ago

This LA study has one of the same authors as the Stanford study (Neeraj Sood). It uses the same test and so it has the same issues with the false positive rate. An honest person would address those but I didn't see that in the press release. This post describes the issues: https://medium.com/@balajis/peer-review-of-covid-19-antibody-seroprevalence-in-santa-clara-county-california-1f6382258c25 https://medium.com/@balajis/peer-review-of-covid-19-antibody... See also this thread: https://news.ycombinator.com/item?id=22924118 https://news.ycombinator.com/item?id=22924118

sjg007 6y ago

Both the LA and Stanford studies are junk. Easily explained by false positives inherent to the test. Stuff like this is why pre-print services can have disastrous consequences. https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...

microdrum 6y ago
So, in your ideal world, we would never do serosurveys for surveillance of low incidence diseases, right? Any Type 1 error is too much Type 1 error, right? I'm sorry that literally all of the seroprevalence data hurt your priors. But the virus is widespread, not very deadly, and people are going to go back to work soon. You can stay home. You will be safe at home.
- VyperCard 6y ago
  No need to be condescending. This is hacker news not Reddit.
DeonPenny 6y ago
That article is junk. Even the fact that it quotes Santa Claras deaths at 100 deaths is wrong because it was only 70 at the time. This entire blog is rife with mathematical and statistical errors.

gok 6y ago

I see a lot of pushback on these studies showing high infection rates. To those people, what rate do you actually believe and why?

skybrian 6y ago
Based on these studies I think >90% of people in California don't have it, and how much higher is unknown.
zucker42 6y ago
There's not enough data to "believe" anything, and most of the pushback is because the studies are methodologically flawed. I think that fatality rate estimates between 0.5% and 1% seem to best match some of the early data on isolated populations, but I'm far from an epidemiological expert. That said, I think people would be a lot more accepting of data contradicting those rates if it didn't have clear issues.
mcnamaratw 6y ago
I feel more informed when I see an infection rate that's substantially higher than the rate of false positives from the test. So the NYC test of pregnant women at (13? 15%?) seems to be much higher than the 1% to 4% range of false positives that people seem to be estimating. But when test results are "down in the noise" I don't feel we're necessarily measuring anything.
robryan 6y ago
I don’t see our squares with our Australian numbers. How have we been able to bring the case numbers right down if there are as many asymptomatic cases and as high an R0 as these studies suggest. Our overall testing of people with symptoms has an under 2% positive rate with one of the highest per capita testing rates in the world. We have a lockdown but it isn’t so extreme as to be able to stop the kind of spread these studies are suggesting. The vast majority of our non imported cases have also been successfully contact traced, people by and large seem to be contracting it from other confirmed cases.

natrik 6y ago

https://covid19tracker.health.ny.gov/views/NYS-COVID19-Tracker/NYSDOHCOVID-19Tracker-Fatalities?%3Aembed=yes&%3Atoolbar=no&%3Atabs=n https://covid19tracker.health.ny.gov/views/NYS-COVID19-Track... 89% of total fatalities in New York have at least 1 comorbidity. I wonder to what extent anyone with unknown cause of death or death due to cancer, but also had COVID-19 gets lumped into the death due to COVID-19 category.

fsh 6y ago
The overall mortality rate in NYC is more than double the usual [1]. I guess that most people above a certain age have at least one comorbidity such as diabetes or high blood pressure. [1] https://www.nytimes.com/interactive/2020/04/10/upshot/coronavirus-deaths-new-york-city.html https://www.nytimes.com/interactive/2020/04/10/upshot/corona...

rdtsc 6y ago

3.4% mortality rate reported by WHO seems to be not as accurate then https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---3-march-2020 https://www.who.int/dg/speeches/detail/who-director-general-... --- Globally, about 3.4% of reported COVID-19 cases have died --- That was used as a basis quite a few decisions, how to treat patients, when to close / open various locations, etc. It does say "reported" in the report, but I think often that part of ignored and many officials assumed it to be as a rate based on infected cases. The article does mention this issue, and I wonder what the new / updated mortality rate is then based on this data.

zucker42 6y ago
I think all the serious scientific papers I've read have long put fatality estimates far below what early WHO press releases suggested.
jsnell 6y ago
I mean, you're tecnically correct in that the number is no longer accurate. But actually the change has been in the other direction. That link is talking about the CFR, not the IFR, and the CFR is up to 7% these days. (170k dead out of 2.5M confirmed cases). No credible source that I saw ever suggested that the IFR was 3%, and that is not what any decisions were based on. Everyone knows that some cases will be missed. The early IFR estimates were all huge ranges like 0.1%-2%, precisely since there was so little information early on about how many cases were not being detected. (And it is surprising how little we've managed to narrow that range down). There are other claims in that WHO link that are obviously wrong in retrospect. E.g. the claim that Covid transmits less efficiently than the flu.

Smoosh 6y ago

Interesting that this article says only 2~3% with antibodies globally. I'm left wondering how reliable the testing (of all kinds) is. https://www.theguardian.com/society/2020/apr/20/studies-suggest-very-few-have-had-covid-19-without-symptoms https://www.theguardian.com/society/2020/apr/20/studies-sugg...

longtimegoogler 6y ago

The Stanford study in Santa Clara that used Premier Biotech appears to be very misleading. Given the confidence intervals on the specificity all 50 positive cases out of the 3330 tested could just be false positives. See Gelman's article on the topic. https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw... I am similarly skeptical of the findings here.

Rury 6y ago
Especially considering the test used here was also, Premier Biotech's. Their manual [1] states, that other coronavirus strains can lead to false positives in the test: >Positive results may be due to past or present infection with non-SARS-CoV-2 coronavirus strains, such as coronavirus HKU1, NL63, OC43, or 229E [1]https://imgcdn.mckesson.com/CumulusWeb/Click_and_learn/Premier_Biotech_COVID19_Package_Insert.pdf https://imgcdn.mckesson.com/CumulusWeb/Click_and_learn/Premi...

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vanniv 6y ago

With the NYC analysis here, everyone is missing one unknowable piece of information. We know that the initial major outbreak in NYC was with a strain from Europe, while the initial major outbreak in California was with an Asia-origin strain. These might be differently dangerous. If the NYC/Europe strain is just 20%-30% more fatal than the Asian one, the maths all start being believable (you start saying that 30-45% of NYC has been infected -- which, unlike 60-100+%, is quite believable. It seems likely that some vulnerable neighborhoods in NY have effectively everyone infected, but that is probably not universally true. It also seems quite believable that we are nearing the point where the majority of folks in NYC have been exposed. If nothing else, the subway is still seeing quite active use, and must be a breeding ground for infection -- and yet, hospitalization has started declining, meaning that new infections are slowing down -- meaning that at least among folks that still go out and about, there must just be fewer people to infect. With subway use still being as high as it is, it seems like it must be true that, amongst the population using it, R could only fall below 1 if herd immunity (in the rider population) was beginning to form. This also jives with the numbers we are seeing, where reported cases are down despite both increased testing and looser counting.

shadowprofile77 6y ago

This recent Swedish study was done in (what seems) to be a way that's much less prone to bias than soliciting people via Facebook posts. It was also based on tests collected from blood donor samples, so none of the specific bias of the Stanford study (which to me also seems like a huge flaw even if other sources of evidence are pointing to similar IFR numbers and undercounting) In any case, the Swedish findings cited for Stockholm in the analysis linked to in this COVID19 subreddit post indicate a similarly low overall IFR of far below 1%. It is worth noting that blood donors would probable tend more towards youth and general good health, which could skew its demographic profile. Also, depending on donors' motives for donating (maybe they thought it would include a COVID test) could skew results in different and unpredictable ways. https://www.reddit.com/r/COVID19/comments/g4znbg/at_least_11_of_tested_blood_donors_in_stockholm/ https://www.reddit.com/r/COVID19/comments/g4znbg/at_least_11...

biolurker1 6y ago

If that's a testing mistake and gives rise to political pressure, it's a disaster

pcdoodle 6y ago

May have been? Quick it with the pandemic porn.