Associations Between Built Environment Factors and SARS-CoV-2 Infections at the Neighbourhood Level in a Metropolitan Area in Germany

Dennis Schmiege; Timo Haselhoff; Salman Ahmed; Olympia Evdoxia Anastasiou; Susanne Moebus

doi:10.1007/s11524-022-00708-5

Associations Between Built Environment Factors and SARS-CoV-2 Infections at the Neighbourhood Level in a Metropolitan Area in Germany

J Urban Health. 2023 Feb;100(1):40-50. doi: 10.1007/s11524-022-00708-5. Epub 2023 Jan 12.

Authors

Dennis Schmiege¹, Timo Haselhoff², Salman Ahmed², Olympia Evdoxia Anastasiou³, Susanne Moebus²

Affiliations

¹ Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany. dennis.schmiege@uk-essen.de.
² Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany.
³ Institute of Virology, University Hospital Essen, University of Duisburg-Essen, 45147, Essen, Germany.

Abstract

COVID-19-related health outcomes displayed distinct geographical patterns within countries. The transmission of SARS-CoV-2 requires close spatial proximity of people, which can be influenced by the built environment. Only few studies have analysed SARS-CoV-2 infections related to the built environment within urban areas at a high spatial resolution. This study examined the association between built environment factors and SARS-CoV-2 infections in a metropolitan area in Germany. Polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infections of 7866 citizens of Essen between March 2020 and May 2021 were analysed, aggregated at the neighbourhood level. We performed spatial regression analyses to investigate associations between the cumulative number of SARS-CoV-2 infections per 1000 inhabitants (cum. SARS-CoV-2 infections) up to 31.05.2021 and built environment factors. The cum. SARS-CoV-2 infections in neighbourhoods (median: 11.5, IQR: 8.1-16.9) followed a marked socially determined north-south gradient. The effect estimates of the adjusted spatial regression models showed negative associations with urban greenness, i.e. normalized difference vegetation index (NDVI) (adjusted β = - 35.36, 95% CI: - 57.68; - 13.04), rooms per person (- 10.40, - 13.79; - 7.01), living space per person (- 0.51, - 0.66; - 0.36), and residential (- 0.07, 0.16; 0.01) and commercial areas (- 0.15, - 0.25; - 0.05). Residential areas with multi-storey buildings (- 0.03, - 0.12; 0.06) and green space (0.03, - 0.05; 0.11) did not show a substantial association. Our results suggest that the built environment matters for the spread of SARS-CoV-2 infections, such as more spacious apartments or higher levels of urban greenness are associated with lower infection rates at the neighbourhood level. The unequal intra-urban distribution of these factors emphasizes prevailing environmental health inequalities regarding the COVID-19 pandemic.

Keywords: COVID-19; Environmental health; Small-scale; Spatial analysis; Urban health.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Built Environment
COVID-19* / epidemiology
Germany / epidemiology
Humans
Pandemics
SARS-CoV-2