Modeling the social and political contexts of United States health protective interventions during the COVID-19 pandemic

The virus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and its disease COVID-19 (Coronavirus Disease 2019) have highlighted the direct relationship between geography and COVID-19; it is a virus that is fostered by the spaces and places in which we live and by the ways in which we occupy and navigate our landscapes. In the early period of the COVID-19 pandemic, it was evident there significant relationships between willingness to adopt preventative health measures and behaviors with prosocial values, the social amplification of risk through friends and family, personal experiences of risk and trust associated with health messaging, and personal individualistic tendencies. Chapter 1 uses data from American Community Survey 2019 5-year estimates and The Behavioral Change COVID-19 (BCC19) Survey to consider the role of voting for Donald Trump in mask-wearing choice during the COVID-19 pandemic in the United States. Accounting for sociodemographic and ecological characteristics, trust in government, approximate time and variation in relative space, and the role of Trump support as an identity characteristic, it finds that voting for Donald Trump in the 2016 presidential election had the greatest effect magnitude and negative relationship with indoor public mask-wearing of any demographic factor or choice measured in the survey, as well as a lower perception of personal risk from the pandemic, and consequently a lower or negative perception of the utility of indoor public mask-wearing. Chapter 2 considers the performance of Bayesian multilevel regression and poststratification with and without a spatial specification in producing small area estimates of first-dose vaccination in the state of California in June 2021 using the The COVID-19 Trends and Impact Survey. A comparison of county-level estimates indicate that inclusion of a spatial smoothing term yields improved results relative to CDC baseline estimates. Chapter 3 builds from findings in Chapter 1 and motivated reasoning theory framework. It uses the BCC19 Survey to identify the social context of Trump supporters' attitudes and beliefs within three areas: political and social engagement; trust of specific information sources to provide reliable information about COVID-19; and geographic proximity of contacts and relative local community social cohesion. It finds that the subset of the population united through Trump support were generally White, non-Hispanic people over the age of 45 years, with high school educations; identified as Christian (most often Evangelical or Protestant); lived in suburban or rural environments; existed within diffuse, county-level friends-driven social networks; felt strongly about the optics of attending political rallies over participating in demonstrations or protests; and preferred domestic public health advice to international. It also suggests that the motivated reasoning pathways associated with Trump support are likely to persist as evidenced with the increasing popularity of other populist politicians.