Caitlin Rivers, PhD+ Your Authors @cmyeaton Outbreak science + epidemiology + health security. Assistant professor at Johns Hopkins Center for Health Security (@JHSPH_CHS). ELBI alum. May. 21, 2020 1 min read + Your Authors

These R(e) estimates are implausibly precise. The credible intervals, if shown, would take up the most of this plot. A move from .89 to .86, in the case of South Dakota for example, is meaningless, even though it’s shown as one of the biggest changes. 1/

Many of these estimations don’t track with available data. Case counts in Alabama and Texas, for example, have mostly been rising so R(e) is very likely above 1. And where are the rest of the states? @C_R_Watson 2/

The analysis is trying to suggest that reopening is safe or even preferred. But most states are rightly moving cautiously. I wouldn’t expect to see a spike from eg opening trails, so it makes sense that trends from pre-reopening wld continue. That's on purpose. 3/

I think it’s fine to track R(e). There are epi modeling groups that have a long history of expertise and do this very well. You’ll notice uncertainty is a key feature of the visualizations on this site. 4/4
 https://epiforecasts.io/covid/posts/national/united-states/ 


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