3 ms·

Balaji Srinivasan had a medium post about this: https://medium.com/@balajis/peer-review-of-covid-19-antibody-seroprevalence-in-santa-clara-county-california-1f

Balaji Srinivasan had a medium post about this: 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... A summary of his post: 1. There were 2 false positives in 401 pre-covid samples (known negative). Assuming a normal distribution, 2 sigma confidence can account for up to 80% of the positive results reported in this study. 2. For the virus to have already infected this many people, it should’ve spread so fast that it doesn’t match what we know about similar epidemics. 3. The researchers recruited volunteers via facebook ads. There could be sampling bias here. I encourage everyone to read the article: my summary < The original article.

Gibbon1 6y ago
My summary is when betting on any test with a low positive rate take under not the over. Saying at least this many people have been infected, wrong. Better. At most this many people have been infected. Reminds me of a survey 15 years ago that said something like 2-3% of black people approved of the job the president was doing. That 2-3% was more likely 'rectified noise'.
- SpicyLemonZest 6y ago
  In normal times, where there aren't critically urgent decisions to be made, that's the right approach. We don't have that luxury right now; we're continually charting the path forward, and if we don't have clean data then we'll need to chart it with unclean data. And I think it's hard to argue that this study is worse than our existing case data, which is simply a daily aggregate of the number of new positive PCR tests labs report they've run. That's not even attempting to be a statistically valid estimate.
viztor 6y ago
for 3, sampling bias would not account for much as the coronavirus will catch you regardless of someone's socio-economical status. The difference is mostly just survival rate.
- Torok 6y ago
  Surely richer people can more effectively self isolate? Less likely to be a key worker, can easily get items delivered to house, more likely to be able to exercise at home etc

Gibbon1 6y ago

My summary is when betting on any test with a low positive rate take under not the over. Saying at least this many people have been infected, wrong. Better. At most this many people have been infected. Reminds me of a survey 15 years ago that said something like 2-3% of black people approved of the job the president was doing. That 2-3% was more likely 'rectified noise'.

SpicyLemonZest 6y ago
In normal times, where there aren't critically urgent decisions to be made, that's the right approach. We don't have that luxury right now; we're continually charting the path forward, and if we don't have clean data then we'll need to chart it with unclean data. And I think it's hard to argue that this study is worse than our existing case data, which is simply a daily aggregate of the number of new positive PCR tests labs report they've run. That's not even attempting to be a statistically valid estimate.

viztor 6y ago

for 3, sampling bias would not account for much as the coronavirus will catch you regardless of someone's socio-economical status. The difference is mostly just survival rate.

Torok 6y ago
Surely richer people can more effectively self isolate? Less likely to be a key worker, can easily get items delivered to house, more likely to be able to exercise at home etc