The Health and Economic Impacts of Nonpharmaceutical Interventions to Address COVID-19: A Decision Support Tool for State and Local Policymakers [book]

Raffaele Vardavas, Aaron Strong, Jennifer Bouey, Jonathan Welburn, Pedro de Lima, Lawrence Baker, Keren Zhu, Michelle Priest, Lynn Hu, Jeanne Ringel
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more » ... issions, please visit The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. Support RAND Make a tax-deductible charitable contribution at For more information on this publication, visit Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2020 RAND Corporation R® is a registered trademark. iii Preface With the rapid spread of coronavirus disease 2019 (COVID-19) and in the absence of evidence-informed guidance, state and local policymakers have put policies in place quickly and with little evidence to support their choices or little consideration of the potentially serious tradeoffs. There is an urgent need for a comprehensive and systematic assessment of potential public health interventions to address COVID-19. In this document, we describe the interdisciplinary and multisectoral approach used to develop a tool to fill that need. The tool provides the information and context that policymakers need now to understand the effects of interventions, weigh the trade-offs between them, and decide when and how these interventions can be relaxed. The tool should be of interest to policymakers and others who wish to use it to understand the potential impacts of various nonpharmaceutical interventions (e.g., school closures, stay-at-home orders) on health and economic outcomes in their communities. This document detailing the methods that underlie the tool will be of interest to policymakers or staff members and researchers who wish to better understand and assess the structure and assumptions of the models and analyses that make up the tool.
doi:10.7249/tla173-1 fatcat:3vvzuwj64janxfydmvlrcludfi