and the risk-to-others curve, against the 0.01x*0.30x quadratic for reference. the risk gets closer to linear the farther out you go.
Expected contribution to spread given number of contacts (assuming 30% transmission risk if positive)
I have no idea how to model the effects beyond this point tbqh. There’s complicated probability dependence among social contacts and I don’t know how to avoid double-counting people who were already infected.
Also keep the Gambler’s fallacy in mind when considering whether to add contacts: If you meet 1 person then the risk is 1%. If you meet 100 people the risk is 63%. If you meet 99 people, confirm you didn’t get covid, and then meet 1 more, your risk is 1%. (Very Approximately because, again, there’s complicated probability dependence among social contacts.)
Here’s that’s risk curve.
and the risk-to-others curve, against the 0.01x*0.30x quadratic for reference. the risk gets closer to linear the farther out you go.
(assuming 30% transmission risk if positive)
I have no idea how to model the effects beyond this point tbqh. There’s complicated probability dependence among social contacts and I don’t know how to avoid double-counting people who were already infected.
Also keep the Gambler’s fallacy in mind when considering whether to add contacts:
If you meet 1 person then the risk is 1%. If you meet 100 people the risk is 63%. If you meet 99 people, confirm you didn’t get covid, and then meet 1 more, your risk is 1%.
(Very Approximately because, again, there’s complicated probability dependence among social contacts.)