School of Architecture, Tianjin Chengjian University, Tianjin, China.
Department of Landscape Architecture, Kyungpook National University, Daegu, Republic of Korea.
Front Public Health. 2023 Feb 28;11:1137489. doi: 10.3389/fpubh.2023.1137489. eCollection 2023.
In late 2019, the coronavirus disease 2019 (COVID-19) pandemic soundlessly slinked in and swept the world, exerting a tremendous impact on lifestyles. This study investigated changes in the infection rates of COVID-19 and the urban built environment in 45 areas in Manhattan, New York, and the relationship between the factors of the urban built environment and COVID-19. COVID-19 was used as the outcome variable, which represents the situation under normal conditions vs. non-pharmacological intervention (NPI), to analyze the macroscopic (macro) and microscopic (micro) factors of the urban built environment. Computer vision was introduced to quantify the material space of urban places from street-level panoramic images of the urban streetscape. The study then extracted the microscopic factors of the urban built environment. The micro factors were composed of two parts. The first was the urban level, which was composed of urban buildings, Panoramic View Green View Index, roads, the sky, and buildings (walls). The second was the streets' green structure, which consisted of macrophanerophyte, bush, and grass. The macro factors comprised population density, traffic, and points of interest. This study analyzed correlations from multiple levels using linear regression models. It also effectively explored the relationship between the urban built environment and COVID-19 transmission and the mechanism of its influence from multiple perspectives.
2019 年末,2019 冠状病毒病(COVID-19)疫情悄然来袭,席卷全球,对人们的生活方式产生了巨大影响。本研究调查了 COVID-19 在纽约曼哈顿 45 个地区的感染率变化以及城市建成环境与 COVID-19 之间的关系。COVID-19 被用作因变量,代表正常情况与非药物干预(NPI)的情况,以分析城市建成环境的宏观(宏观)和微观(微观)因素。本研究引入计算机视觉从城市街景的街景全景图像中量化城市场所的物质空间。然后,研究提取了城市建成环境的微观因素。微观因素由两部分组成。第一部分是城市层面,由城市建筑、全景视图绿色视图指数、道路、天空和建筑物(墙壁)组成。第二部分是街道的绿色结构,由乔木、灌木和草组成。宏观因素包括人口密度、交通和兴趣点。本研究使用线性回归模型从多个层面分析相关性。它还从多个角度有效地探讨了城市建成环境与 COVID-19 传播之间的关系及其影响机制。