Sampling uncertainties aside, this is super sensitive to mis-estimating the false positive rate. Which they seem fairly likely to have done, using an estimated

Sampling uncertainties aside, this is super sensitive to mis-estimating the false positive rate. Which they seem fairly likely to have done, using an estimated test specificity of 100% (with error bars) in one branch of their analysis after getting 30/30 negatives against pre-COVID serum samples. Too small a sample to get that confident in an atypically high specificity, especially if that collection of samples was disproportionately low antibody (e.g. summer blood rather than post cold/flu season blood). That's to my mind the most consequential misestimation of the test characteristics, but Balaji Srinivasan details more: 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...