Department of Architecture and Building Science, Graduate School of Engineering, Tohoku University, Sendai, Japan.
School of Architecture and Urban Planning, Nanjing University, Nanjing, China.
PLoS One. 2024 Oct 16;19(10):e0309019. doi: 10.1371/journal.pone.0309019. eCollection 2024.
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.
先前的研究已经确定了建筑环境与 COVID-19 病例分布之间的几种关联。然而,很少有研究探讨社区层面建筑环境与 COVID-19 之间的非线性关联。本研究以 2022 年 3 月上海 COVID-19 大流行作为案例研究,考察了建筑环境特征与 COVID-19 发病率之间的关系。采用非线性建模方法,即提升回归树模型,来研究这种关系。在社区层面进行了多尺度研究,基于 5 分钟、10 分钟和 15 分钟步行距离的缓冲区。主要发现如下:(1)在邻里层面的分析尺度上,建筑环境变量与 COVID-19 病例分布之间的关系存在差异。(2)建筑环境特征与 COVID-19 病例分布之间存在显著的非线性关联,在不同的尺度上。人口、房价、归一化差异植被指数、香农多样性指数、公共汽车站数量、建筑面积比和与市中心的距离在不同尺度上发挥着重要作用。这些非线性结果从城市规划的角度为不同尺度的大流行应对提供了更精细的参考,并为可持续的 COVID-19 大流行后应对提供了有用的建议。