Abstract:Public health policies such as business closures have been one of our most effective tools in slowing the spread of COVID-19, but they also impose costs. This has created demand from policy makers for models which can predict when and where such policies will be most effective to head off a surge and where they could safely be loosened. No current model combines data-driven, real-time policy effect predictions with county-level granularity. We present a neural net-based model for predicting the effect of busin… Show more
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