OBJECTIVES: The COVID-19 pandemic is a major public health crisis in the United States of America (U.S.). The purpose of this project is to elucidate the impact of various socioeconomic factors, such as population density, ethnicity, median household income, health insurance status and age of the population, on COVID-19-related fatalities in the U.S.

METHODS: Cumulative COVID-19-related fatalities and confirmed cases, as reported by state or local public health departments, were recorded from December 21, 2019 to June 15, 2020. For each state, U.S. Census Bureau and U.S. Bureau of Labor Statistics data points were collected for the analysis (population density, median household income (MHI), percent unemployment, percent African American, and percent disabled). The correlation between the reported socioeconomic factors and the probability of COVID-19-related fatalities was then analyzed via a multivariate stepwise regression analysis at the a=0.05 level.

RESULTS: Multivariate analysis indicated that total population and age-stratified probability of COVID-19-related mortality was significantly related to state population density (total: p<0.001; <65: p<0.001; >65: p<0.001). Unexpectedly, analysis of the probability of COVID-19-related mortality among confirmed cases and total population was negatively correlated with the percent of uninsured Americans (total: p=0.017; cases: p=0.047). Notably, MHI and percent unemployment did not significantly correlate with probability of COVID-19-related fatalities, however both variables were significantly correlated with the percent of uninsured Americans (MHI: p=0.002; percent unemployment: p=0.024).

CONCLUSIONS: State population density was significantly correlated with probability of COVID-19-mortality. An inverse correlation between percent uninsured and the probability of COVID-19-related mortality was observed, which is likely due to limited testing available to uninsured patients and the relative lack of health insurance in individuals less than 65 years of age.