The Imperial team used Diamond Princess data to estimate an IFR of 0.66% (0.2-1.3%) in March That is almost exactly what we see in the serosurveys across the world today, months laterpic.twitter.com/bqEQ7yzX4q
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The Imperial team used Diamond Princess data to estimate an IFR of 0.66% (0.2-1.3%) in March That is almost exactly what we see in the serosurveys across the world today, months laterpic.twitter.com/bqEQ7yzX4q
Pinpointing a specific IFR might be scientifically interesting, but the difference between 0.2% and 0.6% is pretty minimal when it comes to policy, because the impact on health in hard-hit areas is obvious
Massive serosurveys have found, across the board, that very few people are immune to COVID-19, even in hard-hit areas Aside from that, the specific numbers are not nearly as important as people are making them out to be, imo
I don't think this is the whole story, but some people seem to want to turn COVID-19 into some type of math problem where if we just knew what multiple of 'the flu IFR' it is, we would know what to do about it.
I think there is somethign: The number of people already infected. People thought this would go fast, but serosurveys showed that: Nope, not gonna happen.
Yah, agree. Seroprevalence is for...prevalence. Also, for verifying stage of infection since there is a long tail of test positives...
Some of the authors of serosurveys have said they are doing them not just for our policy, but for friends and relatives in the third world. We face a bad economy and some excess deaths due to missed healthcare because of lockdowns. They face starvation.
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