Risk factors for increased COVID-19 case-fatality in the United States: A county-level analysis during the first wave

Abstract

The ongoing COVID-19 pandemic is causing significant morbidity and mortality across the US. In this ecological study, we identified county-level variables associated with the COVID-19 case-fatality rate (CFR) using publicly available datasets and a negative binomial generalized linear model. Variables associated with decreased CFR included a greater number of hospitals per 10,000 people, banning religious gatherings, a higher percentage of people living in mobile homes, and a higher percentage of uninsured people. Variables associated with increased CFR included a higher percentage of the population over age 65, a higher percentage of Black or African Americans, a higher asthma prevalence, and a greater number of hospitals in a county. By identifying factors that are associated with COVID-19 CFR in US counties, we hope to help officials target public health interventions and healthcare resources to locations that are at increased risk of COVID-19 fatalities.

Fig 1. Assessing model fit.

Plots showing (A) half-normal residuals and (B) mean-variance relationship of the observed county-level COVID-19 laCFRs.

Fig 2. Assessing model generality.

Plots showing (A) model outcomes found within the prediction intervals for training data and testing data for the county-level COVID-19 laCFRs and (B) gain curves for training data and testing data for the county-level COVID-19 laCFRs.

Fig 3. Percentage change in COVID-19 laCFR given a 1 unit increase in the variable for each individual variable (shown in black dots) and 95% confidence interval (shown in red), using training data.