A terrific take on what epidemiologists missed (understanding human responses and well-performed serological prevalence studies) and (and done well - vaccines) by @maciekboni
Well worth the read!https://theconversation.com/two-gaps-to-fill-for-the-2021-2022-winter-wave-of-covid-19-cases-156169 …
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It's probably too tempting to make human behavioral change into a just-so story retrospectively, and probably almost impossible to use it as a predictive variable prospectively in the kind of complex environment we have in a pandemic.
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Which is not to say that behavior does not matter! (As I said, that's my bread-and-butter) but it's probably not going to get the analytic bang we seek from it predictively. I suspect we may get an interesting prospective look from detailed mobility data. Not sure we do yet.
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Alternative: society is complex & interaction networks are power law distributed. Many highly connected nodes got infected/immune disrupting network transmission. *BUT* 1) that still means many ppl could still be susceptible, and 2) social networks change w time e.g. with seasons
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The question in the original article was why did epi models miss the relatively rapid, widespread drop? People all masked up/distanced in fear seems less plausible to me as the main explanatory variable given the magnitude, though I think it does matter somewhat.
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