JMIR Publications

ABSTRACT

Background:

COVID-19 has caused over 45,000 deaths in New York City, with a disproportional impact on certain communities. As part of the COVID-19 response, the city has directly administered over six million COVID-19 tests (not including millions of indirectly administered tests not covered in this analysis), at no cost to the individual, resulting in nearly half a million positive results. Given that testing throughout the pandemic has tended to be higher in more affluent areas, these tests were targeted to areas with fewer resources.

Objective:

This study aims to evaluate the impact of this program; specifically, to review its ability to provide equitable testing in economically, geographically, and demographically diverse populations. Of note, in addition to the brick-and-mortar testing sites evaluated here, this program additionally conducted 2.1 million tests through mobile units, to further address testing inequity.

Methods:

Testing data was collected from the in-house Microsoft SQL Server Management Studio 18 Clarity database, representing 6,347,533 total tests and 449,721 positive tests. These tests were conducted at 48 hospital system locations. Per capita testing rates by zip code tabulation area (ZCTA) and COVID-19 positivity rates by ZCTA were used as dependent variables in separate regressions. Median income, median age, percent English speaking, and percent People of Color were used as independent demographic variables, to analyze testing patterns across several intersecting identities. Negative binomial regressions were run in a Juypter Notebook using Python.

Results:

Per capita testing was inversely correlated with median income geographically. The overall pseudo r-squared value when comparing hospital system tests by ZCTA against the selected variables was 0.1101. The number of tests significantly increased as median income fell (SE= 1.00000155, P<.001). No other variables correlated at a significant level with the number of tests. When considering positive tests by ZCTA, positive tests also significantly increased as median income fell (SE= 1.57e-06, P<.001) and as the percentage of females fell (SE= 0.957, P=.001). Positive tests by ZCTA rose at a significant level alongside the percentage of English-only speakers (SE= 0.271, P=.03).

Conclusions:

This program was able to improve equity through the provision of no-cost testing focused in areas of the city that were disproportionately impacted and had fewer resources. By finding higher numbers of positive tests in resource-poor neighborhoods, New York City was able to deploy additional resources such as contact tracing and isolation/quarantine support including free food delivery and free hotel stays early in the course of the COVID-19 pandemic. Equitable deployment of testing is feasible and should be considered early on in future epidemics or pandemics. Clinical Trial: Biomedical Research Alliance of New York (BRANY) Study: 23-15-564, Sponsor ID: RH2023-814, Category: 15-Not Human Subject Research.