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Covid-19 Antibody Seroprevalence in Santa Clara County, California

medrxiv.org

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Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#151

Post by shalmanese »

grandmczeb wrote: post #146
shalmanese wrote: post #112

Earlier quoted context omitted.

How do you square this with 0.14% of all of NYC and 0.25% of all of Bergamo county being dead from confirmed Coronavirus? Surely this puts a strong lower limit on IFR. Deaths in both places can only increase and deaths will inevitably be retroactively assigned a Coronavirus cause.

A large percentage of the population in NYC and Italy have been probably already been infected -- for NYC specifically, I don't think its too implausible to imagine 20-30%. That would give an IFR of ~0.6% which is in line with a lot of other estimates. An IFR of <0.3% seems unlikely though.

That gives a current IFR of 0.6%. Most cases haven't resolved yet and South Korea is showing that the death rate inches up over time as deaths take much longer to resolve than recoveries.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#152

Post by cameldrv »

irq11 wrote: post #143
cameldrv wrote: post #103

Earlier quoted context omitted.

Yes, and look at the way they corrected for this. They rebalanced for demographics, and that doubled their estimate. This is exactly the opposite of what they should have done. For example, zip codes farther from the testing sites were less likely to get tested, and more likely to be positive. What you see is that certain groups were less likely to go get tested, UNLESS they had a good reason to think that they were…

That is just nonsense. You don’t adjust for demographic bias in a sample by conditioning on a second parameter. There’s no universe in which underweighting the underweighted group makes any sense at all. Moreover, there isn any support for the idea that “bored white women” are more or less likely to get tested for symptomatic illness than anyone else. Your entire argument boils down to “I don’t like the implications…

Not in this case. It's basically Simpson's paradox. Honestly I think the study is basically useless, because instead of a random sample, it's a sample of people who, when they saw an ad on Facebook for a free Coronavirus test, decided to sign up, and then actually show up for the test.

The point is that the higher your (voluntary) participation rate is within a group, the less chance you have of selection bias. This goes up to the limit of 100% participation, where you have no selection bias.

What we see in this study is that groups with a lower participation rate (Men, nonwhites, people farther from a testing site) have a higher positivity rate. That is exactly the selection bias we would expect. They then proceed to "correct" the data by undercounting the group (white women that live near a testing site) that has the least selection bias.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#153

Post by cameldrv »

guenthert wrote: post #136
cameldrv wrote: post #103

Earlier quoted context omitted.

Yes, and look at the way they corrected for this. They rebalanced for demographics, and that doubled their estimate. This is exactly the opposite of what they should have done. For example, zip codes farther from the testing sites were less likely to get tested, and more likely to be positive. What you see is that certain groups were less likely to go get tested, UNLESS they had a good reason to think that they were…

With the average adult getting two bouts of common cold each year and mild COVID symptoms resembling a common cold, I'd think a large fraction of the population might think they had it. I wouldn't dear to guess in which way this shifts the estimate. I think it's understood, that with such a small sample size, results are to be taken cautiously. You have to start somewhere though.

There was another serological survey of blood donors in Castiglione d'Adda in Italy. That one came up 70% positive. That town had 1.4% of its population die in March. That suggests an IFR of 2%, not counting people who were sick and might die from COVID in April.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#154

Post by danieltillett »

Animats wrote: post #144
erentz wrote: post #79

It’s hacky and I’m happy to be told how wrong it is. But based on these recent antibody studies in Germany, Finland, and now here in CA, I’ve been assuming an actual fatality rate of about 0.4, and thus an actual infected rate of 250x our known deaths, which is a much firmer number. This is only a small comfort since it means we may have had about 8.75 million infected and presumably now immune in the USA. Or about 2…

There’s still a long way to go in that case. Yes. Stanford's recent study says 2-4% of the population of Santa Clara County has been infected. Those are probably reasonable bounds. Herd immunity is around 80% for this. So about 20 to 40 times as many people need to die before it's over. That test needs to be repeated weekly to get the growth rate. (Preferably not with the scheme from Verity, which requires that you s…

The problem with herd immunity to this virus is how short the immunity to corona virus is - around a year. If we wait for herd immunity to build from low level natural spread then we will never get there.

There is a very major risk with extrapolating the Santa Clara data in the motivation of those being tested has not been controlled. Who is more likely to want to know they have been infected - those who have had classic COVID-19 symptoms or those who haven’t.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#155

Post by JamesBarney »

irq11 wrote: post #143
cameldrv wrote: post #103

Earlier quoted context omitted.

Yes, and look at the way they corrected for this. They rebalanced for demographics, and that doubled their estimate. This is exactly the opposite of what they should have done. For example, zip codes farther from the testing sites were less likely to get tested, and more likely to be positive. What you see is that certain groups were less likely to go get tested, UNLESS they had a good reason to think that they were…

That is just nonsense. You don’t adjust for demographic bias in a sample by conditioning on a second parameter. There’s no universe in which underweighting the underweighted group makes any sense at all. Moreover, there isn any support for the idea that “bored white women” are more or less likely to get tested for symptomatic illness than anyone else. Your entire argument boils down to “I don’t like the implications…

No his argument is that there are two sampling biases.

The demographics of a tested population do not match the demographics of the county.

If someone believes they've been infected they are more likely to seek testing. (self-selection bias)

The study adjusted for the first but not the second bias. He believes the second bias is more important, so when they adjusted for the first they moved the adjusted average farther away from the true average.

I think he's right, self-selection can be a far more impactful bias than things like sex and race.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#156

Post by notforever »

usaar333 wrote: post #63
sxp wrote: post #14

There are similar high infection rates from other semi-randomized samples. https://www.nejm.org/doi/full/10.1056/NEJMc2009316 > Between March 22 and April 4, 2020, a total of 215 pregnant women delivered infants at the New York–Presbyterian Allen Hospital and Columbia University Irving Medical Center . All the women were screened on admission for symptoms of Covid-19. Four women (1.9%) had fever or other symptoms of…

NYC has 30x the per capita death rate of Santa Clara county. Santa Clara county only being 15% as infected is not consistent.

Just a hypothesis, but if being more frequently exposed makes it more likely that the disease will be more severe, then this is plausible. There is some evidence that e.g. doctors/nurses were more likely to die compared to their age cohort, possibly because of higher viral load.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#157

Post by JamesBarney »

notforever wrote: post #156
usaar333 wrote: post #63

Earlier quoted context omitted.

NYC has 30x the per capita death rate of Santa Clara county. Santa Clara county only being 15% as infected is not consistent.

Just a hypothesis, but if being more frequently exposed makes it more likely that the disease will be more severe, then this is plausible. There is some evidence that e.g. doctors/nurses were more likely to die compared to their age cohort, possibly because of higher viral load.

I don't think virologists thing frequency of exposure is very important to lethality. But there is evidence that dosage and stress play a roll which will both be higher in medical personnel.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#158

Post by thu2111 »

DanBC wrote: post #60
microdrum wrote: post #47

Earlier quoted context omitted.

Yep. You've got nothing. CFR is low, and this has been knowable for a long time. You're scared. It's OK. It's illogical and anti-scientific, but it's OK. But you won't be able to hurt ordinary people any longer. Here's Germany's imputed CFR: https://spectator.us/covid-antibody-test-german-town-shows-1... Here's Denmark: https://www.dr.dk/nyheder/indland/doedelighed-skal-formentli... Here's Iceland: https://reason.com…

Why quote Denmark but ignore Sweden? Sweden are doing what you're calling for, and they have pretty high numbers of deaths.

It's not "pretty high", it's middle of the pack and nowhere near the apocalypse that was supposed to be the outcome of their chosen path.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#159

Post by danieltillett »

3fe9a03ccd14ca5 wrote: post #107
jacquesm wrote: post #99

Earlier quoted context omitted.

And last, but definitely not least: you can't draw the conclusion that presence of antibodies equates immunity. It will correlate but there is no guarantee.

Is there a better method?

Yes, but not one that is ethical. You do a challenge experiment to those with antibodies and see if they get infected.

The next best alternative is monitoring a large number of people with antibodies (and a control group) for new infections. This is slow and expensive, but if you have enough people then it will work.

Re: Covid-19 Antibody Seroprevalence in Santa Clara County, California

#160

Post by Gibbon1 »

usaar333 wrote: post #63
sxp wrote: post #14

There are similar high infection rates from other semi-randomized samples. https://www.nejm.org/doi/full/10.1056/NEJMc2009316 > Between March 22 and April 4, 2020, a total of 215 pregnant women delivered infants at the New York–Presbyterian Allen Hospital and Columbia University Irving Medical Center . All the women were screened on admission for symptoms of Covid-19. Four women (1.9%) had fever or other symptoms of…

NYC has 30x the per capita death rate of Santa Clara county. Santa Clara county only being 15% as infected is not consistent.

Take 30 times 0.15 you get 4.5. I wouldn't draw any conclusions due to the low quality of current data.
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