So I've seen these numbers thrown around a lot
I think this analysis is pretty flawed and very likely to be wrong
Some reasons #COVID19 https://twitter.com/ToryFibs/status/1242561095761637376 …
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And despite the fancy language, that's essentially what the authors did. The SIR model they produced is mostly a function of this one assumption
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Now, the authors actually had a good reason for this. They are arguing that it is POSSIBLE that this is true, and we need more testing to ensure that it is not the casepic.twitter.com/hnHwT37Zlg
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However, that is not the message that the media - and most of twitter - have picked up onpic.twitter.com/gsTAdqDlQ3
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Based on all published evidence to date, it is INCREDIBLY UNLIKELY that the hospitalization rate is only 1% for
#COVID19 infections The true rate appears to be quite a bit higherpic.twitter.com/pygB0sP5ay
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What all this noise really shows is how one small assumption can completely change the predicted results of a model
#COVID19Show this thread
End of conversation
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