Exploring the socioeconomic drivers of COVID-19 mortality across various spatial regimes.

Identifying the socioeconomic drivers of COVID-19 deaths is essential for designing effective policies and health interventions. However, how the significance and impact of these factors varies across different spatial regimes has been scantly explored. In this ecological cross-sectional study, we apply the spatial lag by regimes regression model to examine how the socioeconomic and health determinants of COVID-19 death rate vary across (a) metropolitan vs. non-metropolitan, (b) shelter-in-place vs. no-shelter-in-place order, and (c) Democratic vs. Republican US counties. A total of 20 variables were studied across 3108 counties in the contiguous US for the first year of the pandemic (6 February 2020 to 5 February 2021). The results show that the COVID-19 death rate not only depends on a complex interplay of the population demographic, socioeconomic and health-related characteristics, but also on the spatial regime that the residents live, work and play. Household median income, household size, percentage of African Americans, percentage aged 40-59 and heart disease mortality are significant to metropolitan but not to non-metropolitan counties. We identified lack of insurance access as a significant driver across all regimes except for Democratic. We also showed that the political orientation of the governor might have impacted COVID-19 death rates due to the public response (i.e., shelter-in-place vs. no-shelter-in-place order). The proposed analysis allows for understanding the socioeconomic context in which public health policies can be applied, and importantly, it presents how COVID-19 death related factors vary across different spatial regimes.