School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, China.
Front Public Health. 2024 Jan 8;11:1287999. doi: 10.3389/fpubh.2023.1287999. eCollection 2023.
Epidemics are dangerous and difficult to prevent and control, especially in urban areas. Clarifying the correlation between the COVID-19 Outbreak Frequency and the urban spatial environment may help improve cities' ability to respond to such public health emergencies. In this study, we firstly analyzed the spatial distribution characteristics of COVID-19 Outbreak Frequency by correlating the geographic locations of COVID-19 epidemic-affected neighborhoods in the city of Beijing with the time point of onset. Secondly, we created a geographically weighted regression model combining the COVID-19 Outbreak Frequency with the external spatial environmental elements of the city. Thirdly, different grades of epidemic-affected neighborhoods in the study area were classified according to the clustering analysis results. Finally, the correlation between the COVID-19 Outbreak Frequency and the internal spatial environmental elements of different grades of neighborhoods was investigated using a binomial logistic regression model. The study yielded the following results. (i) Epidemic outbreak frequency was evidently correlated with the urban external spatial environment, among building density, volume ratio, density of commercial facilities, density of service facilities, and density of transportation facilities were positively correlated with COVID-19 Outbreak Frequency, while water and greenery coverage was negatively correlated with it. (ii) The correlation between COVID-19 Outbreak Frequency and the internal spatial environmental elements of neighborhoods of different grades differed. House price and the number of households were positively correlated with the COVID-19 Outbreak Frequency in low-end neighborhoods, while the number of households was positively correlated with the COVID-19 Outbreak Frequency in mid-end neighborhoods. In order to achieve spatial justice, society should strive to address the inequality phenomena of income gaps and residential differentiation, and promote fair distribution of spatial environments.
疫情具有危险且难以防控的特点,尤其是在城市地区。明确 COVID-19 爆发频率与城市空间环境之间的相关性,可能有助于提高城市应对此类突发公共卫生事件的能力。在本研究中,我们首先通过将北京市受 COVID-19 疫情影响的街区的地理位置与发病时间点相关联,分析了 COVID-19 爆发频率的空间分布特征。其次,我们创建了一个将 COVID-19 爆发频率与城市外部空间环境要素相结合的地理加权回归模型。然后,根据聚类分析结果对研究区域内不同等级的疫情影响街区进行分类。最后,使用二项逻辑回归模型研究了不同等级街区的 COVID-19 爆发频率与内部空间环境要素之间的相关性。研究结果表明:(i)疫情爆发频率与城市外部空间环境显著相关,其中建筑密度、容积比、商业设施密度、服务设施密度和交通设施密度与 COVID-19 爆发频率呈正相关,而水域和绿化覆盖率与 COVID-19 爆发频率呈负相关。(ii)不同等级街区的 COVID-19 爆发频率与内部空间环境要素的相关性存在差异。低端街区的房价和家庭户数与 COVID-19 爆发频率呈正相关,而中端街区的家庭户数与 COVID-19 爆发频率呈正相关。为了实现空间公平,社会应该努力解决收入差距和居住分化的不平等现象,并促进空间环境的公平分配。