3 ms·
> you'd need to know the false-negative characteristics of the different tests that were used Good point about this. Do we have enough data to compute this?
by eminence32 6y ago
> you'd need to know the false-negative characteristics of the different tests that were used
Good point about this. Do we have enough data to compute this? my layman's guess is that if someone is asymptomatic and receives a negative test, they're not likely to follow it up with another test (which would be one way to learn the first test was a false-negative). But maybe there are other clever ways at getting at the false-negative rate for each type of test.
- pbronez 6y agoMy organization has put together some data on this: https://covidtestdb.com/performance/ https://covidtestdb.com/performance/ We pulled together performance data for dozens of COVID-19 diagnostics, which you can download. We also created a stats tool to help you understand the Predictive Value of each test based on how widespread the disease is in the tested population. The key metrics we look at are: Positive predictive value (PPV), the fraction of positive tests where the person actually had the disease. Negative predictive value (NPV), the fraction of negative tests where the person actually did not have the disease.