Why It’s So Freaking Hard To Make A Good COVID-19 Model

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Why It’s So Freaking Hard To Make A Good COVID-19 Model
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Given the volume of research and data being collected about the novel coronavirus, it seems like answers ought to exist, and there are certainly numbers out there. Trouble is, they’re kind of all over the place. FiveThirtyEight has more:

from the fatality rate in a country where, say, diabetes is less prevalent. The same could be said for the ratesthe U.S. — if the virus spreads in a metro area with many elderly residents, the fatality rate calculated there will be higher than if the epicenter was in a city that skewed younger.

Of course, we probably don’t know the actual fatality rate in those places, anyway. That’s true for a number of reasons, starting with theabout coronavirus cases. Numbers aren’t facts. They’re the result of a lot of subjective choices that have to be documented transparently and in detail before you can even begin to consider treating the output as fact. How data is gathered — and whether it is gathered the same way each time — matters.

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