Maybe I misunderstood something, but is really the odds of getting sick yourself growing linearly?
Let’s say if you meet 1 person the odds of getting corona is 1%. That would mean that meeting 101 people would result in a 101% chance in getting corona. Sure, it is almost linear until you get to about 10 people (in my example), but the curve of risk to get corona should follow something like 1-(0.99)^n if we assume the risk of getting corona is equal from every person you have contact with.
Spreading it linearly with the number of people you meet however I can understand the reasoning behind.
You are correct, but the hope is that the probabilities involved stay low enough that a linear approximation is reasonable. Using for example https://www.microcovid.org/, typical events like a shopping trip carry infection risks well below 1% (dependent on location, duration of activity and precautions etc.).
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.)
Maybe I misunderstood something, but is really the odds of getting sick yourself growing linearly?
Let’s say if you meet 1 person the odds of getting corona is 1%. That would mean that meeting 101 people would result in a 101% chance in getting corona. Sure, it is almost linear until you get to about 10 people (in my example), but the curve of risk to get corona should follow something like 1-(0.99)^n if we assume the risk of getting corona is equal from every person you have contact with.
Spreading it linearly with the number of people you meet however I can understand the reasoning behind.
You are correct, but the hope is that the probabilities involved stay low enough that a linear approximation is reasonable. Using for example https://www.microcovid.org/, typical events like a shopping trip carry infection risks well below 1% (dependent on location, duration of activity and precautions etc.).
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.)