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2/15/2020 09:39:00 PM
Thanks for the feedback! In [this derivation](https://github.com/lots-of-things/wuhan-virus-model/blob/master/Wuhan_to_SF_infection_model.pdf), I walked through the justification for γ and κ in a little more detail. The intuition was to make the recovery+quarantine rate something that decreased as the number of infected increased (mimicking limited healthcare resources). So the recovery rate was originally (β+κ/I)\*I, and then I combined a growth rate, α**,** with the constant term in the recovery rate. So, it ends up declaring that there is a fixed constant additional number of people passively recuperated by the healthcare system independent of the infected population. Maybe not super reasonable, but I'm hoping it looks like a lowest order approximation. It's also a very good idea to see what happens if the "wu" and "sf" coefficients are different. I hadn't thought about it til now, but by conflating the two rate constants in my analysis, I actually lost quite a bit of information. It could be that the γ term in SF plays a much bigger role in the outcome than the one in WU, but my simulations would be blind to that effect. I'll try to add an additional analysis of adding a **𝛿**γ term. I'll update when I try that out.