Neighborhood Disadvantage Measures and COVID-19 Cases in Boston, 2020

Abstract

Objective: Understanding the pattern of population risk for coronavirus disease 2019 (COVID-19) is critically important for health systems and policy makers. The objective of this study was to describe the association between neighborhood factors and number of COVID-19 cases. We hypothesized an association between disadvantaged neighborhoods and clusters of COVID-19 cases.

Methods: We analyzed data on patients presenting to a large health care system in Boston during February 5-May 4, 2020. We used a bivariate local join-count procedure to determine colocation between census tracts with high rates of neighborhood demographic characteristics (eg, Hispanic race/ethnicity) and measures of disadvantage (eg, health insurance status) and COVID-19 cases. We used negative binomial models to assess independent associations between neighborhood factors and the incidence of COVID-19.

Results: A total of 9898 COVID-19 patients were in the cohort. The overall crude incidence in the study area was 32 cases per 10 000 population, and the adjusted incidence per census tract ranged from 2 to 405 per 10 000 population. We found significant colocation of several neighborhood factors and the top quintile of cases: percentage of population that was Hispanic, non-Hispanic Black, without health insurance, receiving Supplemental Nutrition Assistance Program benefits, and living in poverty. Factors associated with increased incidence of COVID-19 included percentage of population that is Hispanic (incidence rate ratio [IRR] = 1.25; 95% CI, 1.23-1.28) and percentage of households living in poverty (IRR = 1.25; 95% CI, 1.19-1.32).

Conclusions: We found a significant association between neighborhoods with high rates of disadvantage and COVID-19. Policy makers need to consider these health inequities when responding to the pandemic and planning for subsequent health needs.

Keywords: COVID-19; geospatial analysis; social determinants of health.

Figure 1

Relationship between neighborhood factors and coronavirus disease 2019 (COVID-19) cases presenting to Massachusetts General Brigham, Boston, February 5–May 4, 2020. (A) Percentage of households living in poverty. (B) Percentage of households receiving Supplemental Nutrition Assistance Program benefits. (C) Percentage of population without health insurance. (D) Percentage of population that is non-Hispanic Black. (E) Percentage of population that is Hispanic. Shading indicates neighborhood characteristic, circles indicate COVID-19 cases, and lines indicate public transit lines. Data sources: Massachusetts General Brigham and American Community Survey.

Figure 2

Relationship between the top quintile (highest percentage) of neighborhood factors and the top quintile (the greatest number) of COVID-19 cases presenting to Massachusetts General Brigham, Boston, February 5–May 4, 2020. Abbreviations: COVID-19, coronavirus disease 2019; SNAP, Supplemental Nutrition Assistance Program. Data sources: Massachusetts General Brigham and American Community Survey.