Geospatial Analysis of Individual and Community-Level Socioeconomic Factors Impacting SARS-CoV-2 Prevalence and Outcomes

Abstract

Background: The SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities.

Methods and findings: All adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2.Among 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized.

Conclusions: This study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.

Figure 1:

Flow diagram of individuals included in analyses of SARS-CoV-2 infection, hospitalization, and death.

Figure 2:

Analysis Flow Chart. FDR = False discovery rate.

Figure 3:

Map depicting the number of individuals per 1,000 population (A) who tested positive for SARS-CoV-2 in the MGB system in Massachusetts and (B) in the Boston area, (C) who were hospitalized at an MGB facility related to SARS-CoV-2, and (D) who died after their hospitalization. Census tracts with fewer than 5 individuals tested are excluded. Only patients tested within the MGB system are represented.

Figure 4:

(A) Conceptual model of an individual’s aggregate risk of disease, arising from the interaction between individual and census tract-level risk factors, with red indicating a positive association with adverse outcomes (increased risk) and green indicating a negative association (decreased risk), and (B) summary of individual characteristics (left) and census tract-level concepts (right) which were independently associated with infection with SARS-CoV-2, hospitalization among those infected, and death among those hospitalized within our study sample, with red indicating a positive association with adverse outcomes (increased risk) and green indicating a negative association (decreased risk). HS = high school.