RESUMO
In response to the rapid spread of the novel coronavirus, SARS-CoV-2, the U.S. has largely delegated implementation of non-pharmaceutical interventions (NPIs) to local governments on the state and county level. This staggered implementation combined with the heterogeneity of the U.S. complicates quantification the effect of NPIs on the reproductive rate of SARS-CoV-2. We describe a data-driven approach to quantify the effect of NPIs that relies on county-level similarities to specialize a Bayesian mechanistic model based on observed fatalities. Using this approach, we estimate change in reproductive rate, Rt, due to implementation of NPIs in 1,417 U.S. counties. We estimate that as of May 28th, 2020 1,177 out of the considered 1,417 U.S. counties have reduced the reproductive rate of SARS-CoV-2 to below 1.0. The estimated effect of any individual NPI, however, is different across counties. Stay-at-home orders were estimated as the only effective NPI in metropolitan and urban counties, while advisory NPIs were estimated to be effective in more rural counties. The expected level of infection predicted by the model ranges from 0 to 28.7% and is far from herd immunity even in counties with advanced spread. Our results suggest that local conditions are pertinent to containment and re-opening decisions.
