"This paper provides a critical review of models of the spread of the coronavirus (SARS-CoV-2) that have been influential in recent policy discussions. It notes potentially important features of the real- world environment that the standard models do not incorporate and discusses reasons why estimating critical parameters is difficult. These limitations may bias forecasts and lead forecasters to overstate confidence in their predictions. They also provide social scientists with opportunities to advance the literature and enable improved policies. This paper also discusses how optimal policies might depend on what is learned from new data and models."

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