Injustices in pandemic vulnerability: A spatial-statistical analysis of the CDC Social Vulnerability Index and COVID-19 outcomes in the U.S.

Background The COVID-19 pandemic has exacerbated health injustices in the U.S. driven by racism and other forms of structural violence. Research has shown the disproportionate impacts of COVID-19 morbidity and mortality in the most marginalized communities. Objectives We examined the associations between COVID-19 cumulative incidence (CI) and case-fatality risk (CFR) and the CDC’s Social Vulnerability Index (SVI), a composite score assessing historical marginalization and thus vulnerability to disaster events. Methods Using county-level data from national databases, we used population density, Gini index, percent uninsured, and average annual temperature as covariates, and employed negative binomial regression to evaluate relationships between SVI and COVID-19 outcomes. Optimized hot spot analysis identified hot spots of COVID-19 CI and CFR, which were compared in terms of SVI using logistic regression. Results As of 2/3/21, 26,452,031 cases of and 448,786 deaths from COVID-19 had been reported in the U.S. Negative binomial regression showed that counties in the top SVI quintile reported 13.7% higher CI (p<0.001) than those in the bottom SVI quintile. Additionally, each unit increase in a county’s SVI score was associated with a 0.2% increase in CFR (p<0.001). Logistic regression analysis showed that counties in the lowest SVI quintile had significantly greater odds of being in a CI hot spot than all other counties, yet counties in the highest SVI quintile had 63% greater odds (p=0.008) of being in a CFR hot spot than counties in the lowest SVI quintile. Conclusion We demonstrated a significant relationship between SVI and CFR, but the relationship between SVI and CI is complex and warrants further investigation. SVI may help elucidate unequal impacts of COVID-19 and guide prioritization of vaccines to communities most impacted by structural injustices.