101–110 of 209 posts
Antibody tests are not as accurate as RT-PCR, but the sensitivity that was observed here was 91% and 99% specificity when compared to confirmed COVID cases. I just want to point out that these researchers are using the corrects tests to do this.
Caveat from the paper: "This study had several limitations. First, our sampling strategy selected for members of Santa Clara County with access to Facebook and a car to attend drive-through testing sites. This resulted in an over-representation of white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian populations, relative to our community. Those imbalances were partly addressed…
Caveat from the paper: "This study had several limitations. First, our sampling strategy selected for members of Santa Clara County with access to Facebook and a car to attend drive-through testing sites. This resulted in an over-representation of white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian populations, relative to our community. Those imbalances were partly addressed…
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 positive. This should cause them to want to underweight the data from the underrepresented groups, but instead they overweighted it.
You can almost say that there were two populations that they were testing: White women who lived near a testing site who thought "what the hell, I'm bored with this quarantine so might as well get my finger pricked", and people who thought "I wonder if that thing I had a few weeks ago was COVID." The number you want is the prevalence from the bored white women. Bored white women might be somewhat skewed from other demographics, but probably not by that much. People who thought they might have had it is a massively skewed group. Effectively their correction removes the bored white women near a testing site, and only counts the people who have reason to think they had COVID.
How is it representative when it's only Facebook users in this sample?
Earlier quoted context omitted.
I keep hearing this sentiment, but I cannot square it with the fact that a non-trivial percent of infected people need to be on ventilators for roughly 20 days. If, back in December, 10k people had what we now know as Covid, there would have been dozens of people on ventilators for weeks at a time in January. The average flu patient needing intubation is only on a ventilator for about 5 days. I just don't see a situa…
All of the flu surveillance numbers suggested a historically bad season this year, and there was a big peak in flu-like mortality in February. It's entirely possible that we were mis-characterizing the data: https://gis.cdc.gov/grasp/fluview/mortality.html
http://med.stanford.edu/news/all-news/2020/04/testing-pooled...
> The researchers found that the burden of COVID-19 in the Bay Area prior to mid-February was low. Only two of nearly 3,000 people with respiratory-disease symptoms who were tested in early 2020 at Stanford Health Care or affiliated clinics for common respiratory viruses were infected with SARS-CoV-2, the virus that causes COVID-19.
Earlier quoted context omitted.
It's known that the vast majority infected do not experience symptoms, or have mild symptoms. I don't think you can draw the conclusion that they had prior immunity.
Not concluding prior immunity but concluding that they now have immunity after having been infected. That is in progress towards herd immunity this number of people actually infected being revealed by these antibody studies is what is interesting. And based on my hacky heuristic described above that is currently around 2.6%. So we are still a long way off herd immunity. But at the same time closer than we thought we…
Yes and no.
A disease is endemic when R0 x S = 1 [0]. R0 for SARS-CoV-2 is estimated to be 2.5 to 3.5 and some models predicting a much higher 5.7 [1].
The herd immunity threshold is given by (1 - S)%, which implies when R0 = 2.5, 60% of the population would need to be immune; similarly 71.42% and 82.45% for R0s, 3.5 and 5.7, respectively.
Saw this comment [1] on Reddit that outlines the limitations of the study well: This is the most poorly-designed serosurvey we've seen yet, frankly. It advertised on Facebook asking for people who wanted antibody testing. This has an enormous potential effect on the sample - I'm so much more likely to take the time to get tested if I think it will benefit me, and It's most likely to benefit me if I'm more likely to h…
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.
"Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics." How is it representative when it's only Facebook users in this sample?
I mean, no. It's not perfect. It will miss demographics like the elderly with lower social media use, but that group tends to be well-sampled already due to their risk profile. It will probably miss some immigrants too, which seems like a bigger problem.
But really, it's a pandemic. It doesn't care about your socioeconomic status. One of its defining qualities is the extent to which it does not cluster in particular communities like more typical epidemics.
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…
https://www.thelancet.com/journals/laninf/article/PIIS1473-3...
I would be surprised if, after this current wave of infections, the percentage of people with antibodies in the US is higher than the low single digits.
Herd immunity without a vaccine is a pipe dream. Our best bet is to massively ramp up testing and contact tracing and really start pushing the number of infections down to a point where parts of society can start functioning again.
"Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics." How is it representative when it's only Facebook users in this sample?
I'm much more concerned about selection bias toward prior sick people; IIRC, Stanford offered to report positive results to the patient.