That said, I have some discount factor in my intuitions but much less than a squared term. Part of the issue is that your (Bayesian) chances of infecting others is not independent of your chances of being infected, a fair fraction of my “probability of being infected” comes from model uncertainty so there’s a substantial error term for correlated reasons to think that we’re in some way wrong about how we are modeling risk.
What’s the best way to give feedback? Your contact page said that tweeting is fine so I just left a small comment there.
I think doing chain analysis is hard because you basically need a full epi model, which isn’t easy to do (especially in places where % infected is low) at an interesting granularity, since (from reading your white paper) your budget/target for model uncertainty seems to be <3x.
I think this is definitely partially true.
That said, I have some discount factor in my intuitions but much less than a squared term. Part of the issue is that your (Bayesian) chances of infecting others is not independent of your chances of being infected, a fair fraction of my “probability of being infected” comes from model uncertainty so there’s a substantial error term for correlated reasons to think that we’re in some way wrong about how we are modeling risk.
Just want to chime in and say
1) yes, we think that thinking about chains of onwards infections is important, and
2) we haven’t done this in great detail, and
3) we would ***LOVE*** if someone wrote up an analysis of this. Issue for it: https://github.com/microcovid/microcovid/issues/17
What’s the best way to give feedback? Your contact page said that tweeting is fine so I just left a small comment there.
I think doing chain analysis is hard because you basically need a full epi model, which isn’t easy to do (especially in places where % infected is low) at an interesting granularity, since (from reading your white paper) your budget/target for model uncertainty seems to be <3x.