Visualizing and Assessing US County-Level COVID19 Vulnerability

Abstract

Objective: Like most of the world, the United States public health and economy are impacted by the COVID19 pandemic. However, discrete pandemic effects may not be fully realized on the macro-scale. With this perspective, our goal is to visualize spread of the pandemic and measure county-level features which may portend vulnerability. Materials and Methods: We accessed the New York Times GitHub repository COVID19 data and 2018 US Census data for all US Counties. The disparate datasets were merged and filtered to allow for visualization and assessments about case fatality rate (CFR%) and associated demographic, ethnic and economic features. Results: Our results suggest that county-level COVID19 fatality rates are related to advanced population age (p <0.001) and less diversity as evidenced by higher proportion of Caucasians in High CFR% counties (p < 0.001). Also, lower CFR% counties had a greater proportion of the population reporting has having 2 or more races (p <0.001). We noted no significant differences between High and Low CFR% counties with respect to mean income or poverty rate. Conclusions: Unique COVID19 impacts are realized at the county level. Use of public datasets, data science skills and information visualization can yield helpful insights to drive understanding about community-level vulnerability.

The Impact of U.S. County-Level Factors on COVID-19 Morbidity and Mortality

“…The spread of COVID-19 at the county level for the U.S. was also studied by assessing the counties’ vulnerability [11,12] or by assessing the effect of countylevel features [13,14,15]. Statistical analysis was the popular approach [13,15,11]; however, some studies used a machine learning approach [14,12]. Counties with a larger percentage of racial and ethnic minorities were affected the most [14,15,13].…”

“…Millett et al [13] found that counties who had a large percentage (greater than 13 percent) of African Americans accounted for more than half of the cases and deaths nationally. Cahill et al [11] found that counties with a lower Case Fatality Rate (CFR) had a greater proportion of the population reporting having two or more races. However, no significant differences were found between High and Low CFR counties with respect to mean income or poverty rate.…”