Responses to Covid-19: Party, Ideology, Health Interests, and State Policymaking (Pre-Recorded)

• In Event: Beyond COVID-19: The Influence of Infectious Diseases on Public Health Policy (Pre-Recorded)

Abstract

In the U.S., state and local governments have been responsible for many public health policies. In the covid-19 pandemic, state officials have been prominent decisionmakers both because of this historic role, as well as because the Trump administration left many details to the states, at the same time that many state officials judged federal policies to be insufficient.

An important question in the empirical analysis of democracies is whether public policymakers respond to the opinions and needs of their populations, and the factors that influence public policy and decisions. Analyzing policy responses to the covid-19 pandemic will contribute to understanding those factors. The spread of an infectious disease and subsequent public health responses also highlight the effects of public and policymaker views on scientific issues, the range of opinions about government interventions, and the impacts of interest groups.

Three models of policy responsiveness each suggest hypotheses. The first model is based on the pattern of the outbreak itself, and the nature of responses to population needs. We have now become accustomed to graphs depicting the growth and decline of the outbreak, including the number of cases, tests, hospitalizations, and deaths. A model of neutral administrative competence suggests that these trends, and associated epidemiologic projections, could be the basis for policymaker decisions, such as orders to close businesses, limit public gatherings, require face coverings, and specify vaccination priorities.

Second, because decisionmakers are elected, politics will play a role in shaping responses to opinions and needs, including party politics in governors' offices and legislatures, as well as general ideological and policy-related views of the public. Researchers have concluded, over a range of policy areas, that the affluent tend to have greater influence compared to other income groups, and that state policymakers may not be responding to the needs of racial/ethnic minority groups. For covid-19 in the U.S., the disease burden has been disproportionately high for African-Americans, Latinos, and low-income communities, and this may have been due to the patterns of politics in the states. An additional element of public opinion and policymaker responses concerns whether there is sufficient trust in the advice of scientific experts, relative to other sources of information and belief, including religious beliefs.

Finally, a model of state-level health policymaking will be incomplete if it does not test for the potential impacts of the health sector itself. The institutions and professionals in the health care sector had a significant interest in how their state governments responded, they faced serious challenges for delivering services during the pandemic, and many health workers themselves were infected by covid-19. The level of their political activity prior to the pandemic, measured through the level of campaign contributions, might influence policymaker responses and, second, the subsequent level of political activity in the sector may also be altered by the experience of the pandemic.

The analysis will examine the time pattern and geographic distribution (observed at the county level for all 50 states) for changes in covid-19 cases, test results, hospitalizations, and deaths. The simplest models propose that policy responses (such as orders to wear face coverings, or to close particular types of businesses) will be based on the time pattern of the disease. More complex models can then incorporate geographic patterns in disease incidence (also observed at the county level), interacting these patterns with residential patterns defined by race, ethnicity, income, and education, to identify systemic inequalities and potential differential responsiveness. Political variables (such as party control, legislative ideology, population partisanship, population opinions with respect to religion and support for science, and health sector political contributions, can then be added to identify the impacts of political characteristics and activity. Finally, the time and geographic basis of the underlying data allows, potentially, for an analysis of the impacts of the policy responses on subsequent disease incidence.

The contribution of this proposed paper is to extend the analysis of policymaking in the context of responses to covid-19, determining both the overall influences on state policy responses, as well as the patterns of differential responsiveness that might be associated with the pluralist politics of elections and interest groups, or with systemic inequalities associated with race, ethnicity, and class.

Author

• Karl Kronebusch, CUNY-Baruch College