County-level demographic, social, economic, and lifestyle correlates of COVID-19 infection and death trajectories during the first wave of the pandemic in the United States

DuPre, Natalie C.; Karimi, Seyed; Zhang, Charlie H.; Blair, Lyndsey; Gupta, Arushi; Alharbi, Lamyaa Mousa A.; Alluhibi, Mariyam; Mitra, Riten; McKinney, W. Paul; Little, Bert

BACKGROUND: The US COVID-19 epidemic impacted counties differently across space and time, though large-scale transmission dynamics are unclear. The study's objective was to group counties with similar trajectories of COVID-19 cases and deaths and identify county-level correlates of the distinct trajectory groups. METHODS: Daily COVID-19 cases and deaths were obtained from 3141 US counties from January through June 2020. Clusters of epidemic curve trajectories of COVID-19 cases and deaths per 100,000 people were identified with Proc Traj. We utilized polytomous logistic regression to estimate Odds Ratios for trajectory group membership in relation to county-level demographics, socioeconomic factors, school enrollment, employment and lifestyle data. RESULTS: Six COVID-19 case trajectory groups and five death trajectory groups were identified. Younger counties, counties with a greater proportion of females, Black and Hispanic populations, and greater employment in private sectors had higher odds of being in worse case and death trajectories. Percentage of counties enrolled in grades 1–8 was associated with earlier-start case trajectories. Counties with more educated adult populations had lower odds of being in worse case trajectories but were generally not associated with worse death trajectories. Counties with higher poverty rates, higher uninsured, and more living in non-family households had lower odds of being in worse case and death trajectories. Counties with higher smoking rates had higher odds of being in worse death trajectory counties. DISCUSSION: In the absence of clear guidelines and personal protection, smoking, racial and ethnic groups, younger populations, social, and economic factors were correlated with worse COVID-19 epidemics that may reflect population transmission dynamics during January–June 2020. After vaccination of high-risk individuals, communities with higher proportions of youth, communities of color, smokers, and workers in healthcare, service and goods industries can reduce viral spread by targeting vaccination programs to these populations and increasing access and education on non-pharmaceutical interventions.