The coronavirus disease 2019 pandemic required significant public health interventions from local governments. Early in the pandemic, RAND researchers developed a decision support tool to provide policymakers with insight into the trade-offs they might face when choosing among nonpharmaceutical intervention levels. Using an updated version of the model, the researchers performed a stress-test of a variety of alternative reopening plans, using California as an example. This article presents the general lessons learned from these experiments and discusses four characteristics of the best reopening strategies.
Keywords: California; Coronavirus Disease 2019 (COVID-19); Epidemiology; Modeling and Simulation; Pandemic; Public Health Preparedness; Robust Decision Making.
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