Inequities in spatial accessibility to COVID-19 testing in 30 large US cities.

Testing for SARS-CoV-2 infection has been a key strategy to mitigate and control the COVID-19 pandemic. Wide spatial and racial/ethnic disparities in COVID-19 outcomes have emerged in US cities. Previous research has highlighted the role of unequal access to testing as a potential driver of these disparities. We described inequities in spatial accessibility to COVID-19 testing locations in 30 large US cities. We used location data from Castlight Health Inc corresponding to October 2021. We created an accessibility metric at the level of the census block group (CBG) based on the number of sites per population in a 15-minute walkshed around the centroid of each CBG. We also calculated spatial accessibility using only testing sites without restrictions, i.e., no requirement for an appointment or a physician order prior to testing. We measured the association between the social vulnerability index (SVI) and spatial accessibility using a multilevel negative binomial model with random city intercepts and random SVI slopes. Among the 27,195 CBG analyzed, 53% had at least one testing site within a 15-minute walkshed, and 36% had at least one site without restrictions. On average, a 1-decile increase in the SVI was associated with a 3% (95% Confidence Interval: 2% - 4%) lower accessibility. Spatial inequities were similar across various components of the SVI and for sites with no restrictions. Despite this general pattern, several cities had inverted inequity, i.e., better accessibility in more vulnerable areas, which indicates that some cities may be on the right track when it comes to promoting equity in COVID-19 testing. Testing is a key component of the strategy to mitigate transmission of SARS-CoV-2 and efforts should be made to improve accessibility to testing, particularly as new and more contagious variants become dominant.

Heterogeneity in Spatial Inequities in COVID-19 Vaccination Across 16 Large US Cities.

Differences in vaccination coverage can perpetuate coronavirus disease 2019 (COVID-19) disparities. We explored the association between neighborhood-level social vulnerability and COVID-19 vaccination coverage in 16 large US cities from the beginning of the vaccination campaign in December 2020 through September 2021. We calculated the proportion of fully vaccinated adults in 866 zip code tabulation areas (ZCTAs) of 16 large US cities: Long Beach, Los Angeles, Oakland, San Diego, San Francisco, and San Jose, all in California; Chicago, Illinois; Indianapolis, Indiana; Minneapolis, Minnesota; New York, New York; Philadelphia, Pennsylvania; and Austin, Dallas, Fort Worth, Houston, and San Antonio, all in Texas. We computed absolute and relative total and Social Vulnerability Index-related inequities by city. COVID-19 vaccination coverage was 0.75 times (95% confidence interval: 0.69, 0.81) or 16 percentage points (95% confidence interval: 12.1, 20.3) lower in neighborhoods with the highest social vulnerability as compared with those with the lowest. These inequities were heterogeneous, with cities in the West generally displaying narrower inequities in both the absolute and relative scales. The Social Vulnerability Index domains of socioeconomic status and of household composition and disability showed the strongest associations with vaccination coverage. Inequities in COVID-19 vaccinations hamper efforts to achieve health equity, as they mirror and could lead to even wider inequities in other COVID-19 outcomes.

Tracking COVID-19 Inequities Across Jurisdictions Represented in the Big Cities Health Coalition (BCHC): The COVID-19 Health Inequities in BCHC Cities Dashboard.

Objectives. To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of the Big Cities Health Coalition (BCHC). Methods. We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities. Results. We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities. Conclusions. This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. (Am J Public Health. 2022;112(6):904-912. https://doi.org/10.2105/AJPH.2021.306708).

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study.

BACKGROUND: Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States. OBJECTIVE: To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic. DESIGN: Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020. SETTING: Chicago, New York, and Philadelphia. PARTICIPANTS: All populated ZCTAs in the 3 cities. MEASUREMENTS: Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models. RESULTS: Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates. LIMITATIONS: The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete. CONCLUSION: Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities. PRIMARY FUNDING SOURCE: National Institutes of Health.