Aaron Lien, Liz Baldwin, and Tom Evans, University of Arizona
Non-pharmaceutical interventions (NPIs), particularly social distancing policies, are the primary policy lever available to state, county, and municipal governments to reduce the transmission of COVID-19. Though NPIs have been widely adopted across the U.S., individual states, counties, and municipalities have taken a diversity of approaches to the implementation of NPIs, ranging from strictly enforced stay-at-home orders to voluntary or recommended strategies that affect highly specific types of businesses. After a year and a half of constantly evolving NPI policies at the state and local level, there is still limited empirical evidence regarding the relative efficacy of mandatory, recommended, or voluntary NPIs or how loosening and lifting NPIs might affect disease spread and the likelihood of resurgence. Existing efforts to track NPIs have not leveraged social science methods to categorize and measure the considerable complexity in policy variation. As a result, epidemiologists are unable to accurately predict how particular implementations of NPIs affect disease spread, and policymakers do not have the information needed to ease restrictions without prompting disease resurgence. There is a critically urgent need for accurate, detailed, and comprehensive measures of NPIs that can be used to inform epidemiological models and provide empirical evidence to support policy decisions. Longer-term, the availability of such measures can be used to support long-range planning of policy responses to future pandemics.
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