👽 - viewfoil

will.stedden > bonkerfield

Viewfoil streams my online communication in one place. It's an experiment to test the limits of my personal transparency. You can connect with me on any of the social sites below.

Connect:

filter: 💡 🐘 🏟 👽🕒🐦 📺 ➿ 💰

👽

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.