I’m curious how I should think about the risk of hanging out with a friend (who is 2x pfizer vaccinated). It seems like a good opportunity for bayesian thinking in the real world, but I’m really unclear how to think about it.
Info: he tested positive on 4 UK lateral flow tests (LFTs), all from the same box (on 2 different days). After this, his roommates took two tests from the same box & both were negative. He has subsequently taken 3 PCR tests + a LFT each day, which have been negative.
[Question] How to bayesian update on multiple covid tests?
I’m curious how I should think about the risk of hanging out with a friend (who is 2x pfizer vaccinated). It seems like a good opportunity for bayesian thinking in the real world, but I’m really unclear how to think about it.
Info: he tested positive on 4 UK lateral flow tests (LFTs), all from the same box (on 2 different days). After this, his roommates took two tests from the same box & both were negative.
He has subsequently taken 3 PCR tests + a LFT each day, which have been negative.
However, false positives seem to be very rare even for LFTs. They’re ~1/1000 (number range from .9968 in original studies to .9997 more recently)
https://www.gov.uk/government/news/new-analysis-of-lateral-flow-tests-shows-specificity-of-at-least-999
https://www.bmj.com/content/372/bmj.n706
But false negatives seem common for everything, including PCRs. It seems there’s a 20-67% false negatives (20% being best it ever gets, on day 8 of infection)
https://www.acpjournals.org/doi/10.7326/m20-1495
https://pubmed.ncbi.nlm.nih.gov/33301459/
Given this, what are the chances he had covid (from maybe 10-20x lower-than-average-risk prior, but in oxford/England)?