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建筑环境对新冠病毒疾病发病率的影响:以华盛顿州金县为例

The impacts of the built environment on the incidence rate of COVID-19: A case study of King County, Washington.

作者信息

Liu Chao, Liu Zerun, Guan ChengHe

机构信息

Department of Urban Planning, College of Architecture and Urban planning, Tongji University, No. 1239, Siping Road, Shanghai, 200092, China.

Urban Science and Policy, NYU Shanghai; Global Network Assistant Professor, New York University Shanghai, No. 1555, Century Road, Pudong New District, Shanghai, 200120, China.

出版信息

Sustain Cities Soc. 2021 Nov;74:103144. doi: 10.1016/j.scs.2021.103144. Epub 2021 Jul 10.

Abstract

With COVID-19 prevalent worldwide, current studies have focused on the factors influencing the epidemic. In particular, the built environment deserves immediate attention to produce place-specific strategies to prevent the further spread of coronavirus. This research assessed the impact of the built environment on the incidence rate in King County, US and explored methods of researching infectious diseases in urban areas. Using principal component analysis and the Pearson correlation coefficient to process the data, we built multiple linear regression and geographically weighted regression models at the ZIP code scale. Results indicated that although socioeconomic indicators were the primary factors influencing COVID-19, the built environment affected COVID-19 cases from different aspects. Built environment density was positively associated with incidence rates. Specifically, increased open space was conducive to reducing incidence rates. Within each community, overcrowded households led to an increase in incidence rates. This study confirmed previous research into the importance of socioeconomic variables and extended the discussion on spatial and temporal variation in the impacts of urban density on the spread of COVID, effectively guiding sustainable urban development.

摘要

随着新冠病毒肺炎在全球范围内流行,当前的研究集中在影响疫情的因素上。特别是,建成环境值得立即关注,以便制定因地制宜的策略来防止冠状病毒的进一步传播。本研究评估了建成环境对美国金县发病率的影响,并探索了在城市地区研究传染病的方法。利用主成分分析和皮尔逊相关系数处理数据,我们在邮政编码尺度上建立了多元线性回归模型和地理加权回归模型。结果表明,虽然社会经济指标是影响新冠病毒肺炎的主要因素,但建成环境从不同方面影响了新冠病毒肺炎病例。建成环境密度与发病率呈正相关。具体而言,开放空间的增加有利于降低发病率。在每个社区内,家庭过度拥挤导致发病率上升。本研究证实了先前关于社会经济变量重要性的研究,并扩展了关于城市密度对新冠病毒传播影响的时空变化的讨论,有效地指导了可持续城市发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bee/8271037/6aef9824aea9/ga1_lrg.jpg

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