As we do serological testing, it is being revealed that the death rate was even lower than previously imagined -- potentially by a factor of 50x [1]. [1] https://www.nature.com/articles/d41586-020-01095-0 Most places (outside of super dense metros) actually don't need quarantine at all. Maybe for people working in eldercare. With these new statistics the risk of death for those <65 is about the same as the normal ris…
They recruited people over Facebook at a time that California's COVID tests were backlogged (with ads not presented in the paper, with links to signup that could, anecdotally, be shared out); in that situation, avoiding selection bias towards people that were sick with something previously and want to know about potential immunity would be rather tough. (Per WTO protocol, they asked about symptoms in their sample but poof for some reason that data isn't in the paper).
They got a 1.5% positive rate in their sample with 50 individuals testing positive. They then immediately applied demographic weighing to move that raw number to around 3%. Only then did they contemplate the false positive rate, taking the data of the manufacturer and 30 samples as a point estimate to figure out a 95% CI of positives around that 3%.
That's a no-no for correctly propagating uncertainty. The statistically legitimate way to do that would've been to generate the 95% confidence interval for belief about the test's false positive rate and carry that forward in the demographic reweighing. That basic math would've avoided the frankly laughable result that a randomly selected person in Santa Clara county could have a 5% chance of having had COVID-19 while in the same county people seeing a doctor and getting tests through their doctor are only around 10% positive for COVID-19 [2].
Another critique: [3]
[1] https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v... [2] https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx#te... [3] https://medium.com/@balajis/peer-review-of-covid-19-antibody...