Socioeconomic and sociodemographic correlations to COVID-19 variability in the United States in 2020 - Golosov, Nikolay; Wang, Shujie; Yu, Manzhu; Karle, Nakul N.; Ideki, Oye; Abdul-Hamid, Bishara; Blaszczak-Boxe, Christopher (Frontiers in Public Health, 2024)
The CDC reports that more than 81% of COVID-19-related deaths are among people aged 65 years and older. The effects of COVID-19 are not homogeneous across populations, varying by socioeconomic status, PM2.5 exposure, and geographic location, which is supported by analysis of existing data as a function of the number of cases and deaths per capita/100,000 persons. We investigate the degree of correlation between these parameters, excluding health conditions and age. We found that socioeconomic variables alone, contribute to ~ 40% of COVID-19 variability while socioeconomic parameters, combined with political affiliation, geographic location, and PM2.5 exposure levels, can explain ~ 60% of COVID-19 variability, per capita when using an OLS regression model; socioeconomic factors contribute ~ 28% to COVID-19-related deaths. Using spatial coordinates in a Random Forest regressor model significantly improves prediction accuracy by ~ 120%. Data visualization products reinforce the fact that the number of COVID-19 deaths represents 1% of COVID-19 cases in the US and globally. A larger number of democratic voters, larger per-capita income, and age greater than 65 – are negatively correlated (associated with a decrease) with the number of COVID cases per capita. Several distinct regions of negative and positive correlations are apparent, which are dominated by 2 major regions of anti-correlation: 1) the West Coast, which exhibits high PM2.5 concentrations and fewer COVID-19 cases; and 2) the middle portion of the US, showing mostly high number of COVID-19 cases and low PM2.5 concentrations. This paper underscores the importance of exercising caution and prudence when making definitive causal statements about the contribution of air quality constituents (such as PM2.5) and socioeconomic factors to COVID-19 mortality rates. It also highlights the importance of implementing better health/lifestyle practices and examines the impact of COVID-19 on vulnerable populations, particularly regarding preexisting health conditions and age. Although PM2.5 contributes to ~7M deaths annually, quantifying any causal contribution toward COVID-19 is nontrivial given confounding factors. This study highlights the need to address, via statistical analysuis, socioeconomic and environmental disparities to better prepare for future pandemics, where policymakers and public health officials can develop targeted strategies to protect vulnerable populations.