> They made an error you'd flunk a first-year statistics student for: ignoring the effect of false positives. I don't think it's fair to say they "ignored" the

> They made an error you'd flunk a first-year statistics student for: ignoring the effect of false positives. I don't think it's fair to say they "ignored" the effect of false positives. The paper very clearly states: > We consider our estimate to represent the best available current evidence, but recognize that new information, especially about the test kit performance, could result in updated estimates.For example, if new estimates indicate test specificity to be less than 97.9%, our SARS-CoV-2 prevalence estimate would change from 2.8% to less than 1%, and the lower uncertainty bound of our estimate would include zero. Some statisticians have accused them of being sloppy with their estimate of their lower uncertainty bound (among other things). The authors have stated that they disagree, and are working to put out additional data to show that their findings are "robust". I honestly don't know (I don't have enough of a background in stats to have an opinion either way), but I look forward to seeing what the authors put out next and how the scientific community responds to it. And more importantly than the results of this single study, I’m looking forward to more antibody testing in the future.