Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Sep 10, 2020
Date Accepted: Nov 27, 2020
Date Submitted to PubMed: Dec 9, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
US County-Level Social Distancing and Policy Effects: A Dynamical Systems Model
ABSTRACT
Social distancing and public policy have been crucial to minimizing the spread of SARS-CoV-2. Strategies for evaluating the effectiveness of policy should take into account the existing dynamics of public behavior absent any policy, including pre-policy social distancing. By modeling time series of county-level GPS-based mobility indices as a system of differential equations, the intertwined dynamics of public behavior, policy effects, and other one-time events are estimated per county in the United States. Parameter estimates show moderate to strong correlations with two relevant census covariates: population density and the proportion of the population living in a rural area per county. Chronological ordering of policies was a strong determinant of their effect, with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived data to further study policy compliance and effectiveness in terms of health outcomes.
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Copyright
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