False precision! Exactly. Even the most sophisticated statistical methods can’t address all bias in these messy data sets. Sometimes we need to focus on the big picture. Trends, rolling averages, triangulating with other studies, viewing everything as an approximation.https://twitter.com/AdamJKucharski/status/1259441470618001409 …
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I wrote this early on about epi models: https://www.theatlantic.com/technology/archive/2020/04/coronavirus-models-arent-supposed-be-right/609271/ … I really hate to see epi models turn into the daily refresh thing we saw run up to the 2016 with election models, rather than "what is the best course of action" guidelines.
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Remember seeing that – really nice piece. Forecasting is such a small part of what models are useful for (especially in outbreaks where control measures change frequently), and as you say, getting lost in details/comparisons distracts from far more important questions
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Tried to get that across in this interview... Tracking Rt is a reasonable way to look at how well states’ intervention strategies are working. However, Dean warns that, on its own, a low Rt is not a good reason to end shelter-in-place measures.https://www.vox.com/recode/2020/4/21/21227855/coronavirus-spreading-by-state-instagram-effective-reproduction-rate …
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“If people are using it for permission to open things back up, it’s not the full story because there are other considerations, like what systems do you have in place to prevent this from shooting back up again,” Dean said. Doesn’t mean anyone is going to listen though!

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And I thought there was model addiction on March 27.... https://cronyclecovid19.substack.com/p/-covid-19-model-addiction-525811 …pic.twitter.com/Fle0UwSWAY
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