Is There a Powerful COVID Infection Rate Predictor?

Interesting Twitter thread about the following question: If you plot the US state-by-state  COVID infection rates since Sept 1, 2020–i.e. the recent and now receding surge–which is a better predictor:

  1. The percent of the population infected before Sept 1, or
  2. The margin of Biden’s victory in the state?

You might expect that states which had lots of COVID before Sept. 1 would have more of it after Sept. 1 for the same reasons they were getting it earlier. Or, I suppose, you might expect the reverse: states learn from their mistakes, and if infection rates were higher earlier then more people have immunity, so there’s a negative relationship between earlier infection rates and later infection rates.

According to Youyang Gu, both of those expectations are broadly wrong:COVID before/after Sept 1 2020

Instead, the single variable with the most predictive power is how strongly states voted for Biden.
COVID Infection vs Biden Vote

As commenters in the thread note, at an R-squared of about 0.5, this is not a fully explanatory variable–there’s a lot going on, no doubt. Youyang Gu’s suggestive claim is only that as single-variable explanations go, this is the most powerful.

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