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[Preprint]. 2021 Feb 26:2021.02.24.21252135.
doi: 10.1101/2021.02.24.21252135.

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

Jess A Millar  1 , Hanh Dung N Dao  2 , Marianne E Stefopulos  3 , Camila G Estevam  4 , Katharine Fagan-Garcia  5 , Diana H Taft  6 , Christopher Park  7 , Amaal Alruwaily  8 , Angel N Desai  9 , Maimuna S Majumder  10
Affiliations

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

Jess A Millar et al. medRxiv. .

Update in

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.

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Conflict of interest statement

6 Conflict of Interest

The author declares that they have no competing interests.

Figures

Exhibit 2.
Exhibit 2.
Assessing model fit. Plots showing (A) mean-variance relationship of the observed county-level COVID-19 laCFRs, (B) half-normal residuals, (C) model outcomes found within the prediction intervals for training data and testing data for the county-level COVID-19 laCFRs, and (D) gain curves for training data and testing data for the county-level COVID-19 laCFRs.
Exhibit 3.
Exhibit 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.
Exhibit 4.
Exhibit 4.
Relationship of each individual significant variable with COVID-19 laCFR over a range of values. To obtain estimates, all other variables were set to their median value in the training data, and the banned religious gatherings variable was set to 0 (indicating religious gatherings were not banned in a county, which account for half of counties included, Appendix A1). Means are shown as solid line black, and 95% prediction intervals are shown as dotted black lines.
See this image and copyright information in PMC

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