Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020

Abstract

Purpose: This ecological analysis investigates the spatial patterns of the COVID-19 epidemic in the United States in relation to socioeconomic variables that characterize US counties.Methods: Data on confirmed cases and deaths from COVID-19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state-level measure of the percent of the population that has been tested for COVID-19 was used to control for the impact of testing. Findings:The impact of COVID-19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID-19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested.Conclusions: Knowledge about the spatial aspects of the COVID-19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to "shelter-in-place" should continue to stem the spread of COVID-19.

COVID-19 incidence and mortality in the Metropolitan Region, Chile: time, space, and structural factors

“…Second, as long as different models are required to tell different stories (34 estimations in this case), a significant part of the municipal variation in infections and deaths can be explained by a rather small number of variables (as inTable 5). In any case, all the results highlight the role of social determinants of health in explaining the dissimilar impact of COVID-19 in the MR as well as other findings in other countries about unequal distribution of COVID-19(83)(84)(85)(86).…”

Decline in Marriage Associated with the COVID-19 Pandemic in the United States

“…Using state-level data ignores population heterogeneity that could obscure the effects of COVID-19 on marriage. Specifically, cases and fatalities in the early COVID-19 experience have been primarily located in large urban areas (Zhang and Schwartz 2020). To focus on marriage in such a setting, we explore marriage data in the Dallas-Fort Worth-Arlington, Texas (DFW) Metropolitan Statistical Area (MSA).…”

United States County-level COVID-19 Death Rates and Case Fatality Rates Vary by Region and Urban Status

“…Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the viral agent of Coronavirus Disease 2019 (COVID- 19). Currently a global pandemic, it was first identified in Wuhan city, Hubei province, China and has since spread worldwide.…”

“…These vulnerabilities, combined with healthcare infrastructure shortfalls, make rural areas potentially high mortality areas [18]. A spatial study found hotspots in COVID-19 incidence and mortality rates per 100,000 in both urban and rural areas [19]. Another study found higher mortality rates per capita in rural, vulnerable counties compared to diverse, urban counties [20].…”