Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February-June 2020, Massachusetts

Abstract

Objectives: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2.

Methods: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts.

Results: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%.

Conclusion: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

Keywords: COVID-19; social vulnerability; spatial analysis.

Figure 1

Indicators and themes in the Centers for Disease Control and Prevention Social Vulnerability Index (SVI). The following indicators and SVI themes were analyzed: socioeconomic status (living below the federal poverty threshold, unemployed aged ≥16 years), household composition and disability (aged ≥65, living with a disability), racial/ethnic minority status and language (racial/ethnic minority, aged ≥5 years with limited English proficiency [ie, who speak English “not well” or “not at all”]), and housing type and transportation (multiunit housing structures [ie, housing with ≥10 units], crowded housing [ie, households with more people than rooms], no vehicle, living in group quarters). Indicators were selected on the basis of a literature review or were excluded because of multicollinearity. Uninsured in the civilian noninstitutionalized population is not a part of the overall SVI or themes but is included in the SVI database as an adjunct variable. Based on the literature, “uninsured” was included in the analysis. Modified and adapted from Agency for Toxic Substances and Disease Registry.

Figure 2

Standardized coefficients of the 4 Social Vulnerability Index (SVI) themes and 11 indicators, by town, Massachusetts, 2018. Values for all 4 themes and indicators were pooled and classified into quartiles. Developed by the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, the SVI is a database and composite index that models social vulnerability in communities in the United States using 15 census-based indicators that capture data in domains of social vulnerability. Values for all 4 SVI themes and indicators were pooled and then classified into quartiles.

Figure 3

Bivariate geographic distribution between the rate of SARS-CoV-2 molecular polymerase chain reaction (PCR) testing and rate of SARS-CoV-2 incidence, by city/town, Massachusetts, February 1–June 17, 2020. Tertiles classification was used to enable comparison of the distribution of the 2 variables (incidence rate and testing rate). Town counts shown for each category. The distribution of confirmed COVID-19 cases is complex and depends on a combination of interacting factors, including socioeconomic conditions, underlying health, health care access, and testing capacity. Comparing a single variable, COVID-19 testing rate is only part of the story and should be interpreted with caution. Data sources: Massachusetts Department of Public Health data from February–June 17, 2010; Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index 2018 for Massachusetts transformed to Massachusetts town level; and University of Massachusetts Donahue Institute.