Thank you Catherio and friends for this incredible work, and the generosity of sharing it. It is super helpful
I have a question: I'm wondering how to reason about the nonlinearity of risk vs group size?
The model assumes risk and group size have a linear relationship, i.e. it is 10x more risky to do an activity with 10x more people.
I don't know how well this approximation holds. Yes, if there are 10x more average people at a party, then there are 10x more infected people. But I may not have meaningfully interactions (e.g. shared airspace) with them all.
I'm assuming at some point whether there's 5,000 or 50,000 people notionally included in the same activity, the risk to me does not increase.
So I'm curious to understand how significant this nonlinearity is. What thinking has already been done on this? What data do we have?
e.g. are there reports that show the upper bound of the number of people that were infected by participating in a single group activity?
I wanted to loop back to this post to say Thank You! for the microcovid project. I wrote up a case study of how we used it.