Socioeconomically Disadvantaged Neighborhoods Face Increased Persistence of SARS-CoV-2 Clusters

Abstract

Objective: To investigate the association between socioeconomic deprivation and the persistence of SARS-CoV-2 clusters. Methods: We analyzed 3,355 SARS-CoV-2 positive test results in the state of Geneva (Switzerland) from February 26 to April 30, 2020. We used a spatiotemporal cluster detection algorithm to monitor SARS-CoV-2 transmission dynamics and defined spatial cluster persistence as the time in days from emergence to disappearance. Using spatial cluster persistence measured outcome and a deprivation index based on neighborhood-level census socioeconomic data, stratified survival functions were estimated using the Kaplan-Meier estimator. Population density adjusted Cox proportional hazards (PH) regression models were then used to examine the association between neighborhood socioeconomic deprivation and persistence of SARS-CoV-2 clusters. Results: SARS-CoV-2 clusters persisted significantly longer in socioeconomically disadvantaged neighborhoods. In the Cox PH model, the standardized deprivation index was associated with an increased spatial cluster persistence (hazard ratio [HR], 1.43 [95% CI, 1.28-1.59]). The adjusted tercile-specific deprivation index HR was 1.82 [95% CI, 1.56-2.17]. Conclusions: The increased risk of infection of disadvantaged individuals may also be due to the persistence of community transmission. These findings further highlight the need for interventions mitigating inequalities in the risk of SARS-CoV-2 infection and thus, of serious illness and mortality.

Keywords: COVID-19; SARS-CoV-2; cluster persistence; socioeconomic inequalities; spatial clustering analysis; transmission dynamics.

Figure 1

Bivariate choropleth map: Relationship between terciles of neighborhood-level deprivation index and of SARS-CoV-2 cluster persistence in the canton of Geneva, Switzerland.

Figure 2

Neighborhood-level socioeconomic deprivation association with SARS-CoV-2 cluster persistence. Kaplan Meier survival estimates of SARS-CoV-2 clusters (600 m spatial window) according to terciles of the socioeconomic deprivation index. The hazard ratio and 95% CI correspond to a deprivation tercile change. The MST-DBSCAN algorithm was run with a maximum spatial distance of 600 m, a minimum time-distance value of 1 day, and a maximum time distance value of 14 days. Similar results were observed using different spatial windows (200, 400, 800, and 1,000 m).