Abstract
In response to the rapid spread of the novel coronavirus, SARS-CoV-2, the U.S. has largely delegated implementation and rollback of non-pharmaceutical interventions (NPIs) to local governments on the state and county level.
This asynchronous response combined with the heterogeneity of the U.S. complicates quantification of the effect of NPIs on the reproductive ratio of SARS-CoV-2 on a national level.
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 the effect of NPIs on the reproductive ratio R_t in 1,904 U.S. counties incorporating implementation, subsequent rollback, and mask mandate efficacy.
We estimate that at some point before Aug 2nd, 2020, 1,808 out of the considered 1,904 U.S. counties had reduced the reproductive ratio of SARS-CoV-2 to below 1.0.
However, on Aug 2nd, the reproductive ration remained below that threshold for only 702 counties.
The estimated effect of any individual NPI is different across counties.
Public school closings were estimated to be effective in metropolitan, urban, and suburban counties, while advisory NPIs were estimated to be effective in more rural counties.
The cumulative prevalence predicted by the model ranges from 0 to 58.6% across the counties examined. The median is 2.6% while the 25th and 75th percentile are 1.3% and 44.6% respectively, indicating that most counties are far from herd immunity.
Our results suggest that local conditions, including socioeconomic, demographic and infrastructural factors, in addition to the cumulative prevalence are pertinent to containment and re-opening decisions.