A lot of the arguments around lockdowns involve circular reasoning. The fact that Region A didn't experience the same crisis as Region B is attributed to Region A's superior policy response, as defined by the excess death count.
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There is such a deep hunger for heroes and villains that it's blinding us to some weird patterns that could provide a useful clue. A disease is not a morality tale.
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The central dogma of the lockdown response—that any large concentration of people not practicing strict social distancing will spiral into an uncontrolled coronavirus outbreak two weeks after they are lifted—is no longer supported all that well by evidence. But it persists.
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The danger is that someplace will test this dogma, nothing very bad will happen to them, and then the measures will become impossible to sustain in the places that do need them (for whatever reason it is that we don't currently understand)
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The problem with framing any specific anti-pandemic measure in strongly moral terms is that you can't walk away from it later without sounding like you're abandoning an ethical principle
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Good question. It could be the role of super spreading events and how they interact with older populations. Mortality is mostly low for covid19 until it hits older or at risk populations. But, Florida has older populations in spades. The CFRs are similar 3.7% FL to 4% CA.
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I'm quite curious about indoor vs outdoor transmission aside from surfaces. Due to wind dispersing them outdoors, particles from the infected likely remain suspended in air for significantly longer in air conditioned indoor environments. This may be a clue for Florida.
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These graphs end too early to be able to capture the effects of the lockdowns. It would take weeks for an effective lockdown to show up in the excess deaths figure. CA locked down on March 19th (Bay Area on the 16th), these graphs end on April 11th.
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I think you're misunderstanding my point. I'm not questioning the efficacy of the lockdowns, which seems universally established.
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agree that policy does not seem to be a good “explainer” of different outcomes in regions. this article talks about different strains prevalent in NY vs WA (https://www.latimes.com/california/story/2020-05-05/mutant-coronavirus-has-emerged-more-contagious-than-original …) irrespective of implied contagion rates. probably need more such explorations
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