Modeling state preferences for Covid-19 policies: Insights from the first pandemic summer

During the COVID-19 pandemic, governments have experimented with a wide array of policies to further public health goals. This research offers an application of multilevel regression with post-stratification (MRP) analysis to assess state-level support for commonly implemented policies during the pandemic.

We conducted a national survey of U.S. adults using The Harris Poll panel from June 17-29, 2020. Respondents reported their support for a set of measures that were being considered in jurisdictions in the U.S. at the time the survey was fielded. MRP analysis was then used to generate estimates of state-level support.

The research presented here suggests generally high levels of support for mask mandates and social distancing measures in June 2020-support that was consistent throughout the United States. In comparison, support for other policies, such as changes to the road environment to create safer spaces for walking and bicycling, had generally low levels of support throughout the country. This research also provides some evidence that higher support for coronavirus-related policies could be found in more populous states with large urban centers, recognizing that there was low variability across states.

This paper provides a unique application of MRP analysis in the public health field, uncovering noteworthy state-level patterns, and offering several avenues for future research. Future research could examine policy support at a small geographic level, such as by counties, to understand the distribution of support for public policies within states.