4/n (FYI - my Bayesian stats are a bit rusty, so please correct me if I'm misunderstanding, but that seems like the simplest explanation of what was done here)
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15/n Now, as ever it is hard to infer causal conclusions from studies like this (correlation=/=causation) BUT This is a careful, well-thought-out attempt to define the benefits associated with each intervention
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16/n For example, I'd say a reasonable conclusion is that the marginal benefit of stay-at-home orders on top of other interventions is probably pretty small Conversely, the benefit associated with closing universities is probably pretty big
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17/n I should also note that I am not an expert in Bayesian statistical methods, so I might've missed something important in terms of limitations of the models used
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18/n Another worthwhile point is that I think that this paper is pretty good, but as with everything I could be wrong Point out any errors I've missed!
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19/n Thread worth reading on some more limitations of the studyhttps://twitter.com/DiseaseEcology/status/1290364813755863041?s=20 …
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Exactly. The aim of masks is to allow other restrictions to be relaxed, to at least some degree. From the methods described, this paper could not detect the effectiveness of masks.
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