AI Article Synopsis

  • Previous studies have linked the built environment to COVID-19 case distribution, but this research focuses on non-linear relationships at the community level using March 2022 Shanghai as a case study.
  • A boosted regression tree model analyzed how various built-environment factors relate to COVID-19 incidence across different walking distances (5, 10, and 15 minutes).
  • Findings highlight that the impact of built environment variables on COVID-19 cases differs by neighborhood scale, with key factors like population density, housing price, and access to public transportation playing important roles in formulating better urban planning and pandemic response strategies.

Article Abstract

Several associations between the built environment and COVID-19 case distribution have been identified in previous studies. However, few studies have explored the non-linear associations between the built environment and COVID-19 at the community level. This study employed the March 2022 Shanghai COVID-19 pandemic as a case study to examine the association between built-environment characteristics and the incidence of COVID-19. A non-linear modeling approach, namely the boosted regression tree model, was used to investigate this relationship. A multi-scale study was conducted at the community level based on buffers of 5-minute, 10-minute, and 15-minute walking distances. The main findings are as follows: (1) Relationships between built environment variables and COVID-19 case distribution vary across scales of analysis at the neighborhood level. (2) Significant non-linear associations exist between built-environment characteristics and COVID-19 case distribution at different scales. Population, housing price, normalized difference vegetation index, Shannon's diversity index, number of bus stops, floor-area ratio, and distance from the city center played important roles at different scales. These non-linear results provide a more refined reference for pandemic responses at different scales from an urban planning perspective and offer useful recommendations for a sustainable COVID-19 post-pandemic response.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11482694PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0309019PLOS

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