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The data from China almost perfectly follows a logistic curve. Unfortunately, extrapolating such a smooth function is pretty much impossible before it starts sa
by fsh 7y ago
The data from China almost perfectly follows a logistic curve. Unfortunately, extrapolating such a smooth function is pretty much impossible before it starts saturating anyway.
- gbrown 7y agoFor sure, but the problem is that innumerable true situations might give rise to a given "observed" logistic curve - something that you can describe with two parameters arose from a mix of incomprehensibly complex transmission dynamics and dauntingly difficult (and often hidden) observation mechanisms. The result is that, even though after the fact we can often achieve a good fit with simple models, there's little reason to expect that simple models would have been generally predictive - the feedback loop even includes the models, since they might inform public health policy! This isn't to say that modelling isn't useful, but that forecasting a novel infection while it's ongoing is really, really, really hard. Edit: Also, I’d be interested to see a comparison of the fit between a typical logistic, four parameter logistic, Gompertz etc. Not all sigmoids are the same.
- AstralStorm 7y agoGompertz type 2 fits somewhat better. Ultimately for such complex things like spread with barriers Tsalis statistics are good. That could mean q-Weibull distribution.
- AstralStorm 7y agoNot even remotely: 1) Number of cases is not flat. Even by now. 2) There was a slowed growth in late cases. It fits Weibull statistics. Late spread is random but responds to distance. (A'la Rayleigh.)