Sure!(1−(1/n))n tends to 1/e as n tends to infinity. That’s the probability of remaining Covid-free (think of it as the probability of never rolling a 19 when rolling a million sided die a million times). Thus the probability of getting Covid during that period is 1−(1/e)
Hm. I can see that being a lower bound, for people getting covid, but I don’t think the 1/n and the power of n are suitably connected for it to be a very accurate estimate.
Though overtime, the number of times to get exposed is going up, and viewing the risk of getting it as going down (as we learn how to mitigate covid risks better) seems to paint a picture with very broad strokes that’s somewhat accurate overall.
If a bunch of people spread out a million microcovids over a year, about 63% will get covid. People assume “wouldn’t they all get it by then?” But to get over 99% it would actually take about 4.6 million microcovids!
Sure!(1−(1/n))n tends to 1/e as n tends to infinity. That’s the probability of remaining Covid-free (think of it as the probability of never rolling a 19 when rolling a million sided die a million times). Thus the probability of getting Covid during that period is 1−(1/e)
Hm. I can see that being a lower bound, for people getting covid, but I don’t think the 1/n and the power of n are suitably connected for it to be a very accurate estimate.
Though overtime, the number of times to get exposed is going up, and viewing the risk of getting it as going down (as we learn how to mitigate covid risks better) seems to paint a picture with very broad strokes that’s somewhat accurate overall.
If a bunch of people spread out a million microcovids over a year, about 63% will get covid. People assume “wouldn’t they all get it by then?” But to get over 99% it would actually take about 4.6 million microcovids!