Abstract -Tom Shafer - Elder Research, Inc
Title: Stay at Home, or at Least Tread Lightly: Using County-Level Data to Study the Effectiveness of COVID-19 Policy
Title: Stay at Home, or at Least Tread Lightly: Using County-Level Data to Study the Effectiveness of COVID-19 Policy
Abstract:
Abstract:
As COVID-19 spread across the U.S. early this year, many agencies at the county, state, and federal levels rushed to enact policies that aimed to slow the disease. Restrictive policies, including many stay-at-home directives implemented across the states, have served as a key form of COVID-19 policy. These measures have been met with varying levels of enthusiasm, but they derive from simple reasoning about how epidemic diseases spread.
As COVID-19 spread across the U.S. early this year, many agencies at the county, state, and federal levels rushed to enact policies that aimed to slow the disease. Restrictive policies, including many stay-at-home directives implemented across the states, have served as a key form of COVID-19 policy. These measures have been met with varying levels of enthusiasm, but they derive from simple reasoning about how epidemic diseases spread.
Elder Research partnered with the Emergent Alliance in early June, working with the U.K. government to study the impact of stay-at-home policies on the spread of COVID-19 and to quantifying the risk of relaxing these orders in favor of a controlled "reopening" plan. In two weeks, our team compiled and modeled a diverse collection of data sets leveraging the U.S.'s geographic, demographic, and political diversity to study whether reopening plans impact the spread of COVID-19 and, by proxy, whether stay-at-home orders themselves are effective. Our work suggests that stay-at-home orders are indeed effective in the mean, but that even the early stages of controlled reopening are less so. Our code, both for data compilation and model fitting, is available on GitHub.
Elder Research partnered with the Emergent Alliance in early June, working with the U.K. government to study the impact of stay-at-home policies on the spread of COVID-19 and to quantifying the risk of relaxing these orders in favor of a controlled "reopening" plan. In two weeks, our team compiled and modeled a diverse collection of data sets leveraging the U.S.'s geographic, demographic, and political diversity to study whether reopening plans impact the spread of COVID-19 and, by proxy, whether stay-at-home orders themselves are effective. Our work suggests that stay-at-home orders are indeed effective in the mean, but that even the early stages of controlled reopening are less so. Our code, both for data compilation and model fitting, is available on GitHub.