California Coronavirus Antibody Studies Likely Wrong That 12.4 Million of New York City's 8.4 Million Residents Have Already Been Infected With the Virus
California and New York coronavirus infection rate estimates differ substantially.

How many Americans have already been infected with the novel coronavirus that causes COVID-19? Answering that question would give public health officials and the rest of us a much better idea of how dangerous the illness is. That information would enable accurate calculations of what percentage of infected people die of the disease, that is, the infection fatality rate.
Right now there are nearly 900,000 confirmed cases in the U.S., but researchers know that potentially a very high percentage of people who have been infected have experienced mild or even symptomless versions of the disease are undetected by the health care system. The best way to figure out the actual percentage of Americans who have already encountered the disease is to do random population screening using antibody blood tests. Three months into the pandemic, the Centers for Disease Control and Prevention (CDC) has yet to fully implement this sort of population screening.
In the absence of widespread testing by the CDC, privately funded researchers associated with Stanford and the University of Southern California earlier this month released the results of two controversial studies in which they tested the blood of residents of Los Angeles and Santa Clara (Silicon Valley) counties for antibodies to the virus. Applying various statistical and demographic adjustments, the California researchers estimated in Santa Clara County that the actual number of residents already infected by early April ranged between 48,000 and 81,000, which would be 50 to 85 times more than the number of confirmed cases. For Los Angeles County they calculated that approximately 221,000 to 442,000 residents have had the infection, which is 28 to 55 times higher than the tally of confirmed cases at the time of the study. If their calculations are right, that would mean that the disease has spread undetected widely throughout the population and would thus be much less deadly than many other researchers had feared.
Applying the lowest (28) and the highest (85) undetected case ratios from the California studies to the 260,000 confirmed cases in New York state would imply that between 7.3 and 22.1 million of the Empire State's 19.5 million residents have already been infected. Applying those ratios to New York City's 146,000 confirmed cases would imply that between 4.1 and 12.4 million of the Big Apple's 8.4 million residents have been exposed to the disease (which, for the upper-end estimate, is obviously impossible).
Yesterday, New York Governor Andrew Cuomo revealed the results of antibody tests of randomly accosted 3,000 New Yorkers tested as they bought groceries and shopped at various locations across 19 counties in 40 localities. The tests suggested that 13.9 percent of New York state and 21.2 percent of New York City residents had been exposed to the virus. That would mean that 2.7 million and 1.8 million state and city residents respectively have been infected with the virus. Stephen Hawes, chair of the University of Washington's department of epidemiology, told the New York Times that he believed it was likely that New York's survey was overestimating the infection rate somewhat by targeting people moving around in society. Folks who are more circumspect about social distancing weren't tested.
Calculations using these New York state and city blood test data suggest that the rate of mild and symptomless coronavirus infections is only about ten to elevenfold greater than the number of confirmed cases in those jurisdictions. Assuming the New York blood test data are reasonably accurate would suggest that the California studies are overestimating undetected infection rates three to eightfold. If Hawes is correct that would mean that the California studies' undetected infection estimates are even less likely to be in the ballpark.
One upshot is that the California studies' relatively low estimates of the percent of infected people who eventually die of the disease—between 0.1 and 0.3 percent—are unfortunately too optimistic.
For more detail, see Jacob Sullum's excellent discussion of why California and New York fatality rates might differ.
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Well, gee, Ron, any chance they differ because one is a socialist paradise of packed together sardines STILL riding germ infested subways, and the other is a socialist paradise spread the hell out and using private cars?
"The coldest winter I ever saw was a summer in San Francisco." - attribution unclear. However, they could plausibly be a Los Angelean (or is it Los Angeleno? I'm a Hoosier so I can never remember that shit) but they almost certainly weren't a New Yorker.
Mark Twain?
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Jacob Sullum goes to an "urban" studies professor for epidemiological information? How about looking at the MIT study linking mass transit to severity and hot spots of outbreak? Maybe looking into why other causes of death in New York have plummeted, is there a financial reason for labeling deaths as COVID19? How about Cuomo's decision to send elderly nursing home COVID19 patients back to their facilities that weren't equipped to handle such cases in large numbers? Also neither CA or NY were providing a try random sampling. the Florida study is much closer to providing a better canvassing of the population. Horrible piece of journalism.
Jacob Sullum goes to an "urban" studies professor for epidemiological information? How about looking at the MIT study linking mass transit to severity and hot spots of outbreak? Maybe looking into why other causes of death in New York have plummeted, is there a financial reason for labeling deaths as COVID19? How about Cuomo's decision to send elderly nursing home COVID19 patients back to their facilities that weren't equipped to handle such cases in large numbers? Also neither CA or NY were providing a try random sampling. The Florida study is much closer to providing a better
random canvassing of the population. I guess when you have an agenda its advantageous to pick to sources that support you narrative.
My thoughts exactly.
This seems a silly take. IFR results for influenza can also vary widely by geographies.
Both studies show our early modeling of how deadly this thing is was off by 10x plus, and that ICU beds required per infection perhaps was even more over-estimated.
This is all very good news.
" (which, for the upper-end estimate, is obviously impossible). "
says someone unfamiliar with the "alternate facts" approach preferred by the Trump administration
Still hiding and cowering in your studio apartment Rev?
My conditions are relatively good. I can work easily if I wish to. I am fortunate enough to have plenty of cushions (provisions, comfort, entertainment, finances). Everyone in my family is healthy. No strong reason to leave the house except to deliver provisions to some people who are better off staying at home.
Plus, my side continues to win the culture war, which pleases me greatly.
How are you?
//I can work easily if I wish to.//
But it's still easier not to, isn't it, father?
//No strong reason to leave the house except to deliver provisions to some people who are better off staying at home.//
And I assume you're goin to jam those "provisions" down their throat?
//Plus, my side continues to win the culture war, which pleases me greatly//
Butt-fucking men is never going to catch on.
"Plus, my side continues to win the culture war, which pleases me greatly."
Keeping us abreast of the culture war score throughout this epidemic is better than anything OBL has ever said. You get the troll of the year award.
Final victory is ever elusive.
He has such disdain for people living in the inner cities in Baltimore, Chicago, Detroit, Los Angeles, and new York.
Perhaps this is because he knows that they are better than him.
Just a wild guess here, but I’m guessing that you have no trouble meeting your financial commitments at the moment.
I have an idea: how about everyone - politicians, social welfare recipients, Social Security recipients, anyone getting money from pensions or any source out all be required to send it into the federal government so they can pay for the essential workers. I mean, we are always together, right?
I wonder how attitudes would change if we did that. My truly calculated guess is we would be open by next Tuesday.
//One upshot is that the California studies' relatively low estimates of the percent of infected people who eventually die of the disease—between 0.1 and 0.3 percent—are unfortunately too optimistic.//
Back to full pessimism, ladies and gentlemen.
No No No, people are getting tested and the testing is curing COVID. That's the underlying message of this article.
Roche evaluated a bunch of the existing COVID antibody tests to see if they could buy one and bring it to market faster/cheaper than they could develop one. Some were absolute garbage, none were reliable enough for commercial production and they've gone in house. Keep in mind that when people initially poo-pooed the FDA for disallowing 'home brew' kits as diagnostic devices, they were doing so specifically because of the issue that Ron is now lamenting.
Previous Ron Bailey articles: Testing IS a Silver Bullet
OK, so it's 10 times the number of infections. That is 9 million based on 900k tested positive. 50k have now died. So that means the rate is 0.56%. And that's based on NY data, which as Sullum indicated is going to be worse. Therefore it is no stretch to say that this will be closer to 0.3% at the end.
A bad flu like season sure. A pandemic that required crashing economies - no way.
Nobody will admit to overreacting and, therefore, the numbers need to be fudged, incessantly, to ensure that the insane overreactions across the country can continue to be sold as a good faith, appropriate reactions.
This means we will have to play the lockdown game every flu season, because seasonal influenza is now teaming up with the coronavirus to kill everyone's grandparents and fat friends.
The more this virus becomes exposed as a joke, the harder the crackdowns are going to get. Government does not like being laughed at, so it will do everything in its power to make sure we are all crying.
Governments do not make mistakes
CM: Just trying to figure out the disease data here. See my colleague Jacob Sullum's trade-off arguments here.
Mr Bailey:
There are too many confounding factors here. First, we are certain that demographics plays a big difference in how serious this disease is. But none of these studies account for differences in demographics. Further, it is known through genetic analysis that the strain of Covid in California likely came directly from China, while the strain in New York came from Europe. The latter is thought to cause more serious problems. Finally, the infrastructure (density, mass transit) and climate differences between the two states are very likely causing different rates of infection.
So using one set of data to confirm/invalidate the other is going to likely be a fool's errand:
New York could have more serious cases per Infected because it is a more deadly disease, or because the infected have higher incidence of comorbitites.
California could have fewer serious/confirmed per infected because the strain is less serious (leading to not notice and spread it more) or because the strain has been in the region longer. (Checking through my work's slack messages, we had a rash of flu like symptoms the last two weeks in January.)
Where are you getting your information about multiple strains of covid19 and there being a difference between the strain of California and New York?
https://www.gisaid.org/epiflu-applications/next-hcov-19-app/
In case the link above is scrubbed out, do a search for gisaid dot org and you can get at it from there. Anyways, the red dots on that tree are cases sampled in the US. The first thing you notice is that there are two big clusters of red dots- one sit in the bottom right, and one set in the upper right. Those are the big breakouts in the US.
And that data tells us some interesting things- The lower right ones came directly from China- and most of the cases are on the west coast. The upper right ones come from several strains that went from china (purple) to Europe (green) and then made it to the US- and the majority of those are in the East Coast, midwest. Notice that the main branches leading to those infections are ones that went through Belgium, France and Spain. Places where the death rate is on the high side for Europe.
Did I miss where the studies said that the California numbers should be applied to New York with its different population densities, groups, etc.?
That's different.
The pandemic never required crashing the economy; the fascist dream of using the crisis as an excuse crashed the economy.
And still is.
Interesting that California's surveys appear to wildly over-inflate the count.
Oh, and apropos of nothing whatsoever, how's that 2020 census count coming along in California?
It is still important to remember that the California cases are a strain of virus that came directly from Asia- probably earlier than the New York strain that came from Europe.
When you look at the impact to Europe, the virus is much more serious- that is, far more people are getting sick. If this is true, then you would expect the number of people noticing the illness and getting tested to be higher compared to the total number of infected. And in California, if the strain is more mild, then more people contracted the virus, didn't notice, and went around spreading it. And in addition, they may have been doing this longer prior to the country being on notice.
The 'experts' at work:
Bird flu pandemic ‘could kill 150m’
James Sturcke
Fri 30 Sep 2005 10.23 EDT
https://www.theguardian.com/world/2005/sep/30/birdflu.jamessturcke
A global influenza pandemic is imminent and will kill up to 150 million people, the UN official in charge of coordinating the worldwide response to an outbreak has warned.
David Nabarro, one of the most senior public health experts at the World Health Organisation, said outbreaks of bird flu, which have killed at least 65 people in Asia, could mutate into a form transmittable between people.
“The consequences in terms of human life when the pandemic does start are going to be extraordinary and very damaging,” he said.
He told the BBC that the “range of deaths could be anything between five and 150 million”.
…Last month Neil Ferguson, a professor of mathematical biology at Imperial College London, told Guardian Unlimited that up to 200 million people could be killed.
“Around 40 million people died in 1918 Spanish flu outbreak,” said Prof Ferguson. “There are six times more people on the planet now so you could scale it up to around 200 million people probably.”
Right, because nothing else was different in 1918 except the population.
The 'experts' at work. We've also had 30 years of "we're all going to die in 20 years" predictions about climate?
The one time 'experts' predicted disaster and we got a disaster? It was the one time we listened to the 'experts'.
Bird flu pandemic ‘could kill 150m’
James Sturcke
Fri 30 Sep 2005 10.23 EDT
https://www.theguardian.com/world/2005/sep/30/birdflu.jamessturcke
A global influenza pandemic is imminent and will kill up to 150 million people, the UN official in charge of coordinating the worldwide response to an outbreak has warned.
David Nabarro, one of the most senior public health experts at the World Health Organisation, said outbreaks of bird flu, which have killed at least 65 people in Asia, could mutate into a form transmittable between people.
“The consequences in terms of human life when the pandemic does start are going to be extraordinary and very damaging,” he said.
He told the BBC that the “range of deaths could be anything between five and 150 million”.
…Last month Neil Ferguson, a professor of mathematical biology at Imperial College London, told Guardian Unlimited that up to 200 million people could be killed.
“Around 40 million people died in 1918 Spanish flu outbreak,” said Prof Ferguson. “There are six times more people on the planet now so you could scale it up to around 200 million people probably.”
https://www.scientificamerican.com/article/mad-cow-sheep-in-britain/
To estimate the potential impact of a sheep epidemic, Neil M. Ferguson and his colleagues at Imperial College, London, considered three possible scenarios. In the best case, BSE does not spread within or between flocks and therefore has a negligable impact on the vCJD epidemic. But at worst, BSE spreads wildly both within and between flocks and raises the vCJD toll from a maximum of 50,000 to 100,000 deaths due to infected cattle alone to a combined total of as many as 150,000 deaths.
https://www.theguardian.com/education/2002/jan/09/research.highereducation
As many as 150,000 people could die from the human form of mad cow's disease, under a "worst-case" scenario of a BSE-infected sheep epidemic, researchers have predicted.
The academics today warned that if BSE has passed from cows to sheep, lamb could pose a much greater brain disease risk than BSE-infected beef, and called for a large-scale BSE screening of the 40m national flock of sheep.
Professor Neil Ferguson, from the Department of Infectious Disease Epidemiology at Imperial College, said: "Our latest analysis shows that the current risk from sheep could be greater than that from cattle, due to the more intensive controls in place to protect human health from exposure to infected cattle, as compared with sheep."
The Imperial College team predicted that the future number of deaths from Creutzfeldt-Jakob disease (vCJD) due to exposure to BSE in beef was likely to lie between 50 and 50,000.
In the "worst case" scenario of a growing sheep epidemic, the range of future numbers of death increased to between 110 and 150,000. Other more optimistic scenarios had little impact on the figures.
https://www.realclearpolitics.com/video/2020/03/27/ezekiel_emanuel_us_will_have_100_million_cases_of_covid-19_in_four_weeks.html
Ezekiel Emanuel: U.S. Will Have 100 Million Cases Of COVID-19 In Four Weeks, Doubling Every Four Days
Posted By Tim Hains
On Date March 27, 2020
Dr. Ezekiel Emanuel, chair of the department of medical ethics at the University of Pennsylvania, warned Friday on MSNBC's "Morning Joe," that based on the current rate of spread, there will likely be 100 million Americans infected by the COVID-19 virus in four weeks.
https://www.express.co.uk/comment/columnists/frederick-forsyth/1270245/coronavirus-neil-ferguson-sars-bird-flu-deaths
And out in the lead here seems to be Imperial College, London, and its pre-eminent guru Professor Neil Ferguson. He was the genius who, on the issue of swine flu, confidently forecast global deaths at four million. The worldwide total turned out to be 18,500. In 2005, Ferguson said that up to 200 million people could die from bird flu. Between 2003 and 2009, just 282 people died worldwide from the disease.
huh, with doubling every 4 days, 4 weeks is 7 doublings, right? that's 2^7 = 128 times the starting number. For it to be 100 million after that, it would have had to start around 780,000. Unless he was saying that we actually had that many cases in late March and a wild undercount, how does that even work?
interesting math in the title. 147% of the people?
D: I hope that folks recognize that it was obviously done tongue-in-cheek.
I realize it was a joke, but then doesn't that show that that isn't how you extrapolate? I mean, suppose the CA results are true and correct; they wouldn't be invalidated by saying that the straightforward extrapolation to NYC is incorrect, right?
On the one hand, it was a "joke." On the other, Bailey still relies on his "joke" to invalidate the result of a study even though it provides at least a partial glimpse into a plausible scenario if we rely on the lower end of the estimates.
So, it doesn't really seem like much of a joke at all. Some would call it clickbait. Others would call it hackery. If it was a joke, nobody got it, and nobody is laughing, except Bailey.
The results of the Stanford study are invalid because the statistical calculations used to obtain them are wrong.
I don't understand all this hate towards Ron Bailey just for reporting and discussing the latest studies. What do all you haters want him to do, wait until the "final" study comes in?
You mean like HCQ?
Explain the logic of applying the NY numbers to CA as authoritative instead of the other way around. And playing some little fallacy games (147% infected, hurr hurr) doesn't negate that.
Yea Bailey is claiming the NY study is authoritative but has no evidence. Likely the two CA studies are reasonably accurate, probably near the low end of their confidence intervals, for their population. The NY study might be correct for its population.
Due to all the confounding factors (e.g. strain, pop density, regional behaviors, etc.) how one can come to the conclusion that both the NY study and the CA studies have to somehow match is proof of his amateurish reasoning. The dude still thinks that the Hockey Stick is good science.
i lol'd.
It worked for global climate warming change, why not for this?
//Applying those ratios to New York City's 146,000 confirmed cases would imply that between 4.1 and 12.4 million of the Big Apple's 8.4 million residents have been exposed to the disease (which, for the upper-end estimate, is obviously impossible).//
So, in true hack fashion, let's stick the implausible upper end of this guesstimate into the headline and ignore the entirely plausible, lower end estimate that makes perfect fucking sense if you've ever spent five minutes in NYC.
I mean seriously, what the fuck? Who writes like this?
Regardless of the margin of error, it can never exceed 100%. Reporting it that way is agenda based or Bailey is an ignorant jackass, take your pick.
Now he says it was tongue-in-cheek, but is that a wise choice for a headline in this environment?
Sigh... **cough**
"I was just keeeding!"
Sure thing.
I'm going with both.
I'm going with Ron's pretty damned smart, considering who all his haters are.
He sure pegged those self-driving cars...
You say that as if anyone has cause to respect your opinion
Stephen Hawes, chair of the University of Washington's department of epidemiology, told the New York Times that he believed it was likely that New York's survey was overestimating the infection rate somewhat by targeting people moving around in society. Folks who are more circumspect about social distancing weren't tested.
I don't know about this. Grocery stores are pretty crowded here (a lot of them are more like corner stores), as are parks. So I'm not sure who, exactly, can be circumspect about social distancing. Combine that with the fact that the employees of those stores routinely commute to different communities, I don't really see why that would be an overestimate.
M: The suggestion is that folks who tend toward greater self-isolation, e.g., tend to shop less, were less likely to be tested and therefore their exposure to infection (likely lower) would not have been accounted for. The reported rate of infection is higher than it would otherwise have been had more self-isolation prone individuals been tested.
Thanks for the answer. I realize that, but my point was basically that there are probably relatively few of those individuals here in NYC.
As I pointed out below, it also fails to count anyone who is symptomatic and following the guideline to self-quarantine. With the rates of infection shown even in the NY study, this real population probably includes a lot more people than any hypothetical circumspect population.
Think about this: every one of the shoppers who tested positive (17%+-) qualifies as an asymptomatic case or else they are in violation of the self-quarantine for the symptomatic.
After I reentered the country and developed a "cold" I hardly ever left my house; now that I've figured out how to do grocery delivery, I still hardly leave. Not sure how many people are in the same boat as me, but that would bias the numbers in the other direction.
The antibody results in NY also showed a huge difference in antibody rates by race and location. 22% for Latinos and blacks and 9% for whites. 22% within NYC/burbs and less than 4% rest of state.
It looks to me like the big difference in antibody results is the obvious one. Those who have been working at the shitty low-paid jobs in medical facilities without PPE and customer-facing jobs have been very heavily exposed to the virus. They really should have gotten much better data re occupations and location re their sample. Esp if they are going to be making macro/policy type judgements re the results
Dude, the whole study seems to have a margin of error somewhere in the neighborhood of 50%. Speculating about racial disparity is just an additional layer of shitting in your pants at this point.
So much for being a man of science. You would much rather panic and point at random statistics until you get one right.
Oh OK. So all the commenters who've been observing that blacks and Latinos have been hit hard with covid19 in NYC are being completely scientific when they attribute that to R-favorable politics. Or that NYC is hit hard and the rest of the state is safe because subways or density or whatever. But when a study points out an alternative explanation - that's pure speculation.
And yes - I know this antibody study is way off. 50% sounds about right. But it's off for everything - not just for some subgroups. And 22% is a hell of long way from either 9% or 4%.
In order to make things fair, we need to infect more whites. I think I finally found some liberal logic to end the lockdowns.
The people most likely to die are elderly people in poorly run assisted living or nursing homes. They do not go grocery shopping.
Stephen Hawes, chair of the University of Washington's department of epidemiology, told the New York Times that he believed it was likely that New York's survey was overestimating the infection rate somewhat by targeting people moving around in society. Folks who are more circumspect about social distancing weren't tested.
Hawes should be immediately fired. The survey is likely still underestimating the infection rate because it failed to target people who are actually symptomatic and are following the guidelines to self-quarantine for 14 days.
Seriously, why do we listen to these fuckwads who clearly have an agenda?
I thought more testing was the cure to COVID?
More testing should be the cure to covid related idiocy. But I'm not all that optimistic. People seem determined to spin everything as justification for more bullshit.
Yeah the testing was supposed to lead to informed decisions, but it's all political. Like always.
Doesn't applying the factor from California to NY need to take into account the difference in testing rates? The rates in NY are 3 times those in California. Wouldn't this make the estimate for NY city more like 1 to 4 million exposed?
So, it seems to me that because this virus is so dramatically more dangerous to the old and infirm, it is likely that death rates will vary quite a bit depending on the conditions that the most vulnerable are likely to live in. It's going to be a lot harder to avoid exposure in NY than in Santa Clara. And it also seems likely that a lot of people in NY were infected in hospitals.
Doesn't imply any problem with the CA studies (which isn't to say there necessarily aren't any).
I sure hope that most New Yorkers have been exposed. That seems like the best news we could hope for right now. This thing just needs to spread. No fucking way we can keep living like this for months without dire social and economic consequences.
Also because of the big age differential in how the virus hits, for most people under 50, the chance of dying from it is probably more like .01%. There are loads of things more likely to kill me every day. I'll take those chances. Most people would if they hadn't been fed awful and misleading fear-mongering stories for the past two months.
I sure hope that most New Yorkers have been exposed. That seems like the best news we could hope for right now.
Yeah, the cat is out of the bag. The lockdowns are nothing but an attempt to test the populations' willingness to follow orders at this point.
I'm glad we are starting to get to the bottom of the numbers. But, we really didn't need all these numbers, or lockdowns, because we had a fairly good sense that this was really only dangerous for the old and infirm, and mostly nothing to worry about for younger, healthier people … just like every other respiratory illness we've lived with for the past 70 years.
It's not like our baseline before we obtained more data was "Oh shit, this is killing everyone, completely randomly, and at very high rates." And, yet, that is how we reacted to it. Our hearts ran away with our brains.
Yup. That's pretty much what I've been saying.
What really puzzles/disgusts me is how readily people have apparently just accepted that this is what you do for a pandemic. It absolutely fucking isn't. There have been loads of pandemics in the 20th century and this reation is really unprecedented. I'm uncomfortable with any forced quarantine, but at least there is precedent for that when you are quarantining people likely to be infected. Quarantining the whole population is unprecedented and ridiculous and, as far as I can tell, an unconstitutional and illegal power grab. This cannot be allowed to become the "new normal".
This cannot be allowed to become the “new normal”.
#normalnormal
you'd think we'd at least stop quarantining the people with antibodies
The California study "[applied] various statistical and demographic adjustments". Unless you use the exact same algorithm to make demographic adjustments to the NY study's raw data, comparing the results is pretty meaningless. You can't just copy the calculated ratio from California and paste it onto NY. There are confounding factors that wouldn't be accounted for.
You can if you're a moron and write for Reason.
Asymptotes, how do they work?
A healthy body is constantly fighting off infection, both viral and bacterial. The body does thss by producing anti-bodies. The best case scenario would be the antibodies fight off the disease without showing any symptoms.
That does not always work, of course, sometimes the disease has an effect on the body, and you get "sick," meaning showing symptoms. Which can vary from mild, to moderate, to severe, to life threatening.
But there are definitely a large group of people who were infected by the disease, their bodies fought it off well, and they experienced no symptoms. These studies suggest that there are many such people.
I just realized that, according to statistics, in 3 weeks when I turn 50, I will be 10x more likely to die if I catch the virus. Better to get it now at 49 before the odds change! If you are currently infected, please contact me immediately. #heightenthecurve #betteroffinfected
You just need to start looking at the numbers for over/under age 60 and you will be safe(r) again.
The NY antibodies test obviously did not count the school going children who may have been exposed at a higher rate than adults before the schools were closed. And they are presumably more asymptomatic than adults. Adding this group to the study will increase the ratio of NYers in my opinion.
NY saying 13.9% statewide as of 4/19 to 4/20... it never goes down, might be a couple percent higher now.
Confirmation-to-infection ratios are meaningless unless confirmation testing used consistent standards (impossible, even within states) and dealt with the same strains (very unlikely)... extrapolating from CA to NY on the basis of such ratios makes even less sense.
Looks more and more like the Swedes were right, exposure rate is much higher than thought even in areas with low death conts, perhaps because milder strains avoid straining hospitals and spread more easily. More and more immune will slow the spread further.
Interesting how much resistance there is to the dozen or more studies estimating infection rates from 10-50%, some people just do not want to hear this. But if critics can't find a common systemic flaw across multiple kinds of tests, they are soon going to be buried under the mountain of evidence.
Yeah, you can criticize one study, but we are starting to get pretty comparable results from lots of different places. Many countries in Europe that have done more broad testing are also coming up with something around .1-.2%.
Agree.
All of the studies done thus far are remarkably consistent in the same direction (15-20% have antibodies in a given population), we don't need to continue to harp on this particular one. I would also add that just about everyone who is going to be exposed has been at one point while going to one of the "essential" businesses or through someone who has.
That raises another question - do the majority have some sort of cross-immunity from other coronavirus exposures? Are some people just not sensitive to it at all due to genetics? There's no way to answer either of those questions that I can think of.
have not seen any refererences on whether cross-immunity from other coronas is possible or likely... might be another explanation for the death patterns
on the plus side, immunity is likely to last at least a year
https://www.statnews.com/2020/04/20/everything-we-know-about-coronavirus-immunity-and-antibodies-and-plenty-we-still-dont/
Some folks don't want to hear good news especially those who want this crap to continue ad infinitum. This is nothing but good news - the news is so good we should be done with all these ridiculous lockdowns at once. The more good news like this comes out the more the tyrants (tyrants always double down when wrong) will push the boot on your head, until, well, people fight back.
What will it take, besides a college statistics class, to convince people that the analysis in the Stanford study is just wrong.
You should be putting 0 weight in the results of the Stanford study; it has undebatable errors in its analysis.
I believe they were going to release another paper soon that addresses some of the issues with the analysis.
Yeah, I've heard that too, but in the meantime they haven't publicly retracted their claims and instead released another study (the L.A. study) via a press release, with no accompanying methodological information. How long is too long for time-sensitive mistakes to remain uncorrected by the authors?
I don't know, but I've seen some comments from the people who did the study and they are taking the criticisms seriously. Hopefully we'll see something soon.
Just FYI: The researchers keep assuring me that their responses taking into account the criticisms are imminent. We shall see.
All well and fine, but you should put weight in all the studies that have followed (and similar ones in Europe) that are all directionally the same, even if the numbers may seem high.
Millions upon millions have been exposed due to the lockdowns funneling folks into the same stores, so something else is at play with folks that have not developed antibodies. There can be several theories on this.
Which specific studies are you talking about and what do you mean by "directionally the same"? I'm actually curious and not just trying to argue.
The L.A. county one isn't a good example because it's by the same authors as the Stanford study, presumably makes the same mathematical mistakes, and doesn't have any publicly available methodology information.
The NYC study was consistent with previous knowledge about fatality rates.
The only slightly promising study for the "significantly lower than expected IFR" hypothesis is the just released (literally in the last hour) Miami study, but there's not much information on it yet.
Meanwhile we have a plethora of studies showing 0.5% IFR or slightly higher is probably accurate.
These are the only studies of total infected in the United States. You can't measure IFR otherwise.
Good try.
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Before application of the factors from CA studies, wouldn't there be a need to do some kind of adjustment to account for differing percentages of the total population having been tested already? The ratio for L.A. County couldn't possibly apply in Iceland or South Korea because a much higher percentage of the populations in those places were tested already, but in CA the testing has still pretty much only been done on people who presented with syomptoms at a hospital, and for maybe the first 2-3 months of the virus spreading (assuming it actually started here sometime in January), even that wasn't enough if you hadn't been in contact with someone "fresh off the boat" from Wuhan. With the comparative loads at the hospitals in CA (where talk of how to deal with that situation is still prefaced with the word "if") vs NYC, it seems likely that a far greater percentage of NYC residents overall have been tested for the virus directly. Also, COVID getting into nursing homes in CA so far doesn't seem to be happening as often as it seems to be in NYC and surrounding areas, so it's possible that the NYC numbers are skewed relative to CA by virtue of a higher rate of exposure among their high-risk populations.
This is not going to b easy but we'll keep fighting and w'll win this battle.
Sure. Thank God the virus is now disappearing!
Could it indicate that California took it serious sooner then New York? They should check and see how much damage Pelosi did around Chinatown encouraging crowds and advising people to dine and party and shop.
In March DeBlasio, Cuomo and their health department was still claiming New York had nothing to fear and the President was just overreacting. For a City that had 3 daily flights from Wuhan what were they thinking? China shut down travel within China from Wuhan but not international.
It is starting to look like the US was infected in December and even more in January before we knew what hit us. China allowed 1.5 million people to fly out of Wuhan after banning travel from Wuhan to any place in China. Is it surprising the world is infected?
There are two closely related problems. One, the current tests have way too many false positives and false negatives. And two, nobody really is quite sure what the false positive and false negative rates are. In other words, these tests are barely better than nothing, All these calls for mass testing miss this fact.
Look at the QA/QC for both SC and LA anti-body tests. The false positive rate is very low and in any event, they adjusted for it.
If we have a shutdown in America between 1 and 325 million Americans will contract covid and between 1 and 325 million will die. If we don't have a shutdown, between 1 and 325 million will contract covid and between 1 and 325 million will die. Globally those numbers will be between 1 and 7.5 billion, respectively. Got it now?
What a convoluted, terrible headline. There are plenty of reasons that account for the differences in numbers, but to pretend that a CA study said 12.4 million NYC residents are infected is dishonest at best.
They may be overestimating the cases of the infected, but they are also overestimating the death cases.
The CDC has issued guidelines in March according to which if it was ASSUMED that someone had Covid-19 without an actual positive test, they could be put down as a death due to Covid-19.
They then re-issued those guidelines a few weeks later with a more nebulous language but which still did not strictly require a positive Covid-19 test for a doctor to classify a death as a Covid-19 death.
THAT's is the primary problem here. Strange, that reason is completely oblivious to this.
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My point might seem odd at first; but what if a researcher removed "nursing home" deaths from the New York and California studies?
I understand that this could look like "cooking" the data to lower the death rate; but if you consider the fact that the instances where is the virus rips through a nursing home and kills a lot of people is to some degree an "artificial" environment where the disease is let loose upon the most vulnerable.
My understanding is that about a quarter of the New York deaths were in such facilities... I don't know about LA or SF.
Maybe I'm slow or missing something but can explain to me how 12.4 million be infected in a population of 8.4? Where's the difference of 4 million?
He said it was impossible. That’s extrapolating the highest possible number by multiplying that percentage by New York’s population. It should limit at 100% if you’re being genuine, but not if you’re trying to be a jerk, as the author clearly is.
He's not trying, it comes naturally.
I have worked in Manhattan for the past 40 years, with the past 12 of them working in an office at Rockefeller Plaza. I have started to notice over the past 2 to 3 years, if not longer, there is no off season when it comes to tourists. They are ALWAYS around - every day, every month. Whether the transmission of Covid came via China tourists or European tourists, we'll never have the definitive answer. However, I'm almost positive New York's high rate of infections are due to its density and the influx of tourists year round.
Maybe somebody already mentioned this, but one explanation for the discrepancy could be that the rate of testing per capita is quite different between NY and CA. According to the worldometers site, NY state is at 3.7 tests per 100 residents, and I would guess that New York county is even higher. CA has a below-average number of tests per 100 residents, but I can't find data about the number of tests in LA county. Assuming that the number of tests per capita (and the correlated number of confirmed cases) is much higher in NY than in LA, it's apples and oranges to compare the rates of infection to confirmed cases in both places.
I'm a libertarian-leaning science professor with too much time on his hands lately, and I find all of this analysis very interesting. Thanks for the articles, Ron! We're still very early in the process of discovering the true nature of the epidemic - the analysis this month of the infection prevalence reminds me of the arguments over exponential curves last month. Hopefully with more data and more analysis we'll get to the bottom of this.
The survey results were that 5% of those tested in LA and 20% of those tested in NY were positive. That is not surprising given what we know about the two places.
Sensationalist criticism suggesting that the ratio of previously-diagnosed to actual cases in LA should have been extrapolated to NY (but wait, that means more than 100% of the population is infected!) is silly. We all understand that prior to these surveys, New Yorkers were much more heavily tested than Californians.
agree. the results don't imply things
god bless american
This is a worthless article. The CA researchers were clear that their study was not dispositive. So what? The randomized study I. Z ew York, which would automatically be more rigorous just based on the fact that it’s covering far more subjects in a randomized fashion shows 21.2% (1.8M) infected at @ 4/11. With a mortality rate of 5%, that is 90,000 dead, in New York City, it’s an antibody test, which means these people had it and fought it. They are out shopping and living life, not on a ventilator. So why is it that there are only 10,000 dead? Where are the other 80,000? Why is the actual death rate only about 0.5%? Why should we all live in fear for a bad flu?
Since the primary efficient method of transmitting the virus is droplets of water from coughing or sneezing, how is it possible for a person with no symptoms to spread the virus beyond a trivial percentage? The virus becomes unviable after a relatively short period on things people touch.
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You lose credibility when you do the math wrong and try to use that to disprove someone else.
You lose credibility when you do the math wrong and try to use that to discredit someone else.
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I think it’s very wrong to assume that New Yorkers shopping for groceries are somehow reckless and more likely to have contracted corona. EVERYONE is going out for groceries or to park—if not work. Those who aren’t shopping are probably home sick, in a hospital, prison, nursing home or morgue. I think well over 22% in NYC have gotten it. And the tests seem to give more false positives if the cases were recent. (So I read) They found 15% of women giving birth were actively positive at Columbia Presbyterian. And that was end of March into early April. I would think 9 month pregnant women would be among those NOT out. Anecdotally, I think 30-50% easily. I think there’s a vested interest in underestimating cases to cover for fact lockdowns don’t really work and the death rate isn’t nearly as high as feared.