Understanding the effects of county- and state-level pandemic-era policy changes on behavioral health in the U.S.

Principal Investigator

Rita Hamad

Director, Social Policies for Health Equity Research Center, T.H. Chan School of Public Health, Harvard University

Co-Investigators

 

  • Kaitlyn Jackson, Senior Statistical Analyst, T.H. Chan School of Public Health, Harvard University
  • Thomas Carton, Director of Analytics, Louisiana Public Health Institute
  • Amy Chiang, Research Specialist, Department of Medicine, University of California, San Francisco
  • Mark Pletcher, Professor, Department of Epidemiology and Biostatistics, University of California, San Francisco
  • Guangyi Wang, Research Associate, Department of Social and Behavioral Sciences, T.H. Chan School of Public Health, Harvard University
  • Emily Wright, Postdoctoral Research Fellow, SPHERE Center, T.H. Chan School of Public Health, Harvard University

Funded By

National Institute of Mental Health (NIMH)

The problem:

During the COVID-19 pandemic, public health, economic, and social policies were designed to mitigate health threats, but these policies may also have mitigated or exacerbated health inequities. Because COVID-related policies vary extensively from county to county, it has been difficult for researchers to assess the impact of these policies on health, mental health, and socioeconomic outcomes.

The approach:

To better understand the impact of COVID-related policies, Hamad and colleagues built the U.S. COVID-19 County Policy (UCCP) Database, which contains data on 27 policies—gathered weekly from a random sample of 309 U.S. counties across all 50 states and Washington, D.C.—implemented from January 2020 to December 2021. The 27 policies can be broken out into three categories:

1. containment and closure policies, such as school or workplace closures;

2. economic response policies, such as income, food, or housing assistance; and

3. public health policies, such as testing and contact tracing.

Counties in the UCCP Database represent more than half of the U.S. population and are diverse with respect to geography, race, ethnicity, and political climate. The random sample includes an overrepresentation of nonmetropolitan counties and counties ranked higher on the CDC’s Social Vulnerability Index, which identifies communities that will most likely need support before, during, and after a public health emergency.

The team finished collecting data in December of 2023. The UCCP Database is now publicly available through ICPSR for other researchers to download and use.

With this database, the team analyzed the longitudinal trajectories of local county policymaking activities during the COVID-19 pandemic. Using Pearson’s correlation coefficient, the team mapped positive and negative linear correlations between policies.

The findings:

Plotting counties’ containment and closure policies demonstrates that many policies were enacted and revoked simultaneously.

Plotting counties’ economic policies demonstrates that most counties maintained nutrition support policies from early 2020 through 2021. However, the proportion of counties with income support dropped by about half in mid 2021.

Plotting counties’ public health policies demonstrates that health campaigns, testing, and contact tracing policies were in place from early 2020 through 2021, while vaccine passport requirements increased after vaccine rollout.

Containment and closure policies were strongly correlated with one another, but were less correlated with economic policies and moderately negatively correlated with public health policies.

The team’s next aim is to access and link behavioral health survey data with the county policy data to evaluate county-level policy effects on mental health, mental healthcare utilization, and substance use, among other outcomes.

A heat map labeled “Inter-policy correlation.” The heat map plots the Pearson’s correlation coefficient, ranging from 0.97 to -0.3, among individual county-level COVID mitigation policies within and across three domains—contain and closure, economic, and public. The correlation among many UCCP policies was high to moderate. Containment policies had a positive correlation with each other, but they have a less significant correlation with economic policies and a moderately negative correlation with public health policies.

Selected Publications & Presentations

Hamad, R., Lyman, K. A., Lin, F., Modrow, M. F., Ozluk, P., Azar, K. M. J., Goodin, A., Isasi, C. R., Kitzman, H. E., Knight, S. J., Marcus, G. M., McMahill-Walraven, C. N., Meissner, P., Nair, V., O’Brien, E. C., Olgin, J. E., Peyser, N. D., Sylwestrzak, G., Williams, N., … Carton, T. (2022). The U.S. COVID-19 County Policy Database: a novel resource to support pandemic-related research. BMC Public Health, 22(1), 1882. https://doi.org/10.1186/s12889-022-14132-6

Batra, A., Jackson, K., & Hamad, R. (2023). Effects Of The 2021 Expanded Child Tax Credit On Adults’ Mental Health: A Quasi-Experimental Study. Health Affairs, 42(1), 74–82. https://doi.org/10.1377/hlthaff.2022.00733

Jackson, K. E., Chiang, A. Y., & Hamad, R. (2024). The association of increased SNAP benefits during COVID-19 with food insufficiency and anxiety among US adults: a quasi-experimental study. Public Health Nutrition, 27(e186), 1–11. https://doi.org/10.1017/S1368980024001447