[Question] Does there exist a detailed Bayesian COVID tracker?

[bounty: $100 for recommending a tool that I use for more than two weeks]

I would love (and happily pay for) a piece of software that I could tell (a) a bunch of recent interactions between people (“Alice, masked, spent 3 hours, indoors, distanced, with Bob, unmasked, on Nov 1”), and (b) a bunch of evidence about their health over time (“Dolores tested negative on Nov 3″), and make queries about how likely various people are to have COVID.

I’d want it to be capable of complicated inferences like “Alice met with Bob yesterday; Bob met with Charlie 4d ago; Charlie separately met with Dolores that same day. Dolores just tested negative; given that, Alice is now less likely to be incubating COVID.”

Ideally, it would take into account things like contagiousness-over-time profiles, and incubation periods, and asymptomatic cases, and how all those things differ between people, and tests’ false negative rates—but I realize that’s a lot to ask.

Some non-solutions:

  • https://​​microcovid.org is great at what it does, but what it does is analyze individual activities, not make inferences between people and across time.

  • ^ The associated MicroCOVID spreadsheet does better on this front, but (AFAICT) doesn’t capture correlations between people’s risk levels, or make inferences like “Zelda tested negative, therefore all the microcovids she inflicted over the last couple weeks should be somewhat discounted.”

  • Privacy-conscious COVID tracking apps can’t offer the level of sophistication I want. I want to be able to account for masked-ness and ventilation, which flatly isn’t captured by “How many pings did Alice’s phone hear from Bob’s?”