As Covid-19 began to take off in the U.S. early this year, federal, state, and county governments hurried to contain it. Policies restricting movement, closing businesses, etc., have become a staple of government policy, including many stay-at-home directives across the U.S. These measures have been met with varying levels of enthusiasm, but they are rooted in an understanding about how epidemic diseases spread. Now, with several months of data, we can begin to test whether these policies have been effective in their primary function and to what extent a controlled “reopening” raises a community’s COVID-19 risk profile.
This post first appeared on Elder Research Data Science & Machine Learning Blog, please read the originial post: here