Is Covid-19 community level testing effective in reaching at-risk populations? Evidence from spatial analysis of New Orleans patient data at walk-up sites

• Published in: BMC public health Vol. 21; no. 1; p. 632
• Main Authors: Hernandez, Julie H, Karletsos, Dimitris, Avegno, Jennifer, Reed, Chantell H
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 01-04-2021; BioMed Central; BMC
• Subjects: Accessibility; Adaptation; Adolescent; Adult; African Americans; Aged; At risk populations; Availability; Census; Cities; Community planning; Coronaviruses; Coverage; COVID-19; COVID-19 - diagnosis; COVID-19 Testing; Datasets; Demographic aspects; Demographic variables; Demographics; Demography; Ethnicity; Evaluation; Female; GIS; Health care facilities; Health Services Accessibility; Humans; Immunization; Low income groups; Male; Mathematical analysis; Medical screening; Methods; Metropolitan areas; Middle Aged; Minority & ethnic groups; Neighborhoods; New Orleans; Population; Populations; Public health; Race; Refrigeration; Spatial Analysis; Vaccination; Vaccines; Vulnerable Populations; Young Adult; New Orleans; Cities; Louisiana; Orleans Parish Louisiana; United States > US; GIS; New Orleans; Coverage; Accessibility; Covid-19; Vulnerable populations
• DOI: 10.1186/s12889-021-10717-9
• EISSN: 1471-2458

This paper evaluates the increase in coverage and use of Covid-19 testing services for vulnerable and hard-to-reach populations through the introduction of community-based walk-up sites in New Orleans, LA. While most GIS work on Covid-19 testing coverage and access has used census tract or ZIP code aggregated data, this manuscript is unique in that it uses individual level demographics and exact addresses to calculate distances actually traveled by patients.
We used testing data recorded for 9721 patients at 20 sites operating in May-June 2020. The dataset includes detailed age, race and ethnicity, and testing results as well as the exact address of each individual. Using GIS, we estimated changes in testing coverage for minority neighborhoods and calculated the actual distance covered by individuals. Logistic regression and multivariate linear regression were used to identify socio-demographic variables associated with distance travelled to and used of nearest testing site. We used a secondary dataset from drive-through sites to evaluate change in coverage at the census tract level for the metropolitan area.
Walk-up sites significantly increased testing availability in New Orleans, and specifically in minority neighborhoods. Both African Americans and Asians were more likely (14.7 and 53.0%) to be tested at the nearest walk-up site. They also covered shorter distances to get tested. Being elderly was also significantly and positively associated with testing at the nearest site. Hispanics, however, were not associated with increased proximity to and use of nearest sites, and they traveled an additional 0.745 km to get tested. Individuals who tested positive also travelled significantly longer distances to obtain a test.
Walk-up sites increased testing availability for some vulnerable populations who took advantage of the sites' proximity, although inequalities appear at the metropolitan scale. As cities are planning community vaccination campaigns, mobile, walk-up sites appear to improve both coverage and accessibility for hard-to-reach populations. With adequate technical (vaccine dose refrigeration) and messaging (addressing reticence to immunization) adaptations, they could constitute a key complementary approach to health facility points of delivery.