Longitudinal disparities in social determinants of health and COVID-19 incidence and mortality in the United States from the three largest waves of the pandemic

Abstract

The United States experienced at least five COVID-19 waves linked with different mutated SARS-CoV-2 variants including Alpha, Delta and Omicron. In addition to the variants, the intensity, geographical distribution, and risk factors related to those waves also vary within socio-demographic characteristics and timeframes. In this project, we have examined the spatial and temporal pattern of COVID-19 in the USA and its associations with Social Determinants of Health (SDoH) by utilizing the County Health Rankings & Roadmaps (CHRR) dataset. Our epidemiologic investigation at the county level showed that the burden of COVID-19 cases and deaths is higher in counties with high percentages of smoking, number of preventable hospital stays, primary care physician rate, the average daily density of PM_2.5 and percentages of high proportions of Hispanic residents. In addition, the analysis also demonstrated that COVID-19 incidence and mortality had distinct characteristics in their association with SDoH variables. For example, the percentages of the population 65 and older had negative associations with incidence while a significant positive association with mortality. In addition to the elderly population, median household income, unemployment, and number of drug overdose deaths showed a mixed association with COVID-19 incidence and mortality. Our findings validate several influential factors found in the existing social epidemiology literature and highlight temporal associations between SDoH variables and COVID-19 incidence and mortality not yet frequently studied.

Keywords: COVID-19 waves; Generalized estimating equations; Health disparities; Multiple regression; Social determinants of health; Spatiotemporal analysis.