We were told to "flatten the curve." Everybody understood that the area under the curve would be the same, i.e. total infections would be the same. The goal was to avoid spiking over the line -- the line being health care resources. We did.
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Yes, there must be, but I haven't figure out what it is. I mean, everything from an SIR model to the most complex agent-based simulations yields this result. The bottom line is that e.g. flu (R0=~1.4) infects a smaller portion of the population than e.g. measles (R0>10)...
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...before the epidemic peters out. Flattening the curve reduces R0. Is that assumption I'm making? Or is it unclear why a disease with smaller R0 infects fewer total people?
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A great many, it is clear. The same critique applies to you in spades.pic.twitter.com/0aCyv5za7U
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Keep in mind herd immunity threshold = 1-1/R0. If one does nothing, R0≈3 thus threshold ≈65%, with overshot ≈80% of the population gets infected. If you flatten the curve and get R0 down to ≈1,5, then threshold ≈35%, even w/ overshot ≈40% of the population gets infected.
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Think of it as making the disease less infectious. If the probability of a contagious person infecting another person goes down, then you'll need fewer people infected for the epidemics start to slow down and eventually fade off.
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Social distancing reduces the area under the curve if maintained until zero sources of community spread exist. Or a vaccine is developed. Otherwise, the same number of persons are infected. Think the famous Sidney Harris "and then a miracle occurs" cartoon applies here.
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@CT_Bergstrom completely neglects the price we pay for the curve flattening and R0 reduction. It's as if is for free. No buddy, it doesn't come for free. Rampant poverty causes untold many more deaths, stress & despair than not flattening the curve the way we did.Thanks. Twitter will use this to make your timeline better. UndoUndo
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