Li Sui, Li Zhe, Dong Yixin, Shi Tiemao, Zhou Shiwen, Chen Yumeng, Wang Xun, Qin Feifei
School of Architecture and Planning, Shenyang Jianzhu University, Shenyang, Liaoning, 110168 China.
Institute of Ecological Urban Planning and Green Building, Shenyang Jianzhu University, Shenyang, Liaoning, 110168 China.
Build Simul. 2023;16(5):683-699. doi: 10.1007/s12273-022-0918-8. Epub 2022 Aug 10.
Respiratory infection is the main route for the transmission of coronavirus pneumonia, and the results have shown that the urban spatial environment significantly influences the risk of infection. Based on the Wells-Riley model of respiratory infection probability, the study determined the human respiratory-related parameters and the effective influence range; extracted urban morphological parameters, assessed the ventilation effects of different spatial environments, and, combined with population flow monitoring data, constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells. In the empirical study in Shenyang city, a severe cold region, urban morphological parameters, population size, background wind speed, and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios. The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant. The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables. At the same time, the change in human body spacing beyond 1 m had a minor influence on the risk of infection. Among the urban morphological parameters, building height had the highest correlation with the risk of infection, while building density had the lowest correlation. The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results. The overlap rate between medium or higher risk areas and actual cases was 78.55%. The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements. The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.
呼吸道感染是新型冠状病毒肺炎的主要传播途径，研究结果表明城市空间环境对感染风险有显著影响。基于呼吸道感染概率的威尔斯-莱利模型，该研究确定了与人类呼吸相关的参数及有效影响范围；提取了城市形态参数，评估了不同空间环境的通风效果，并结合人口流动监测数据，构建了一种评估城市尺度网格单元中新冠病毒呼吸道感染风险的方法。在严寒地区沈阳市的实证研究中，利用城市形态参数、人口规模、背景风速和个体行为模式，计算了不同情景下城市区域网格中时空伴随风险的分布特征。结果表明，城市公共空间中呼吸道感染风险与上述变量之间的相关性显著。在这些变量中，暴露时间对呼吸道感染风险概率的影响程度最大。同时，人体间距超过1米时的变化对感染风险的影响较小。在城市形态参数中，建筑高度与感染风险的相关性最高，而建筑密度的相关性最低。利用沈阳市在2022年3月至4月疫情的实际点位分布对评估结果进行验证，中高风险区域与实际病例的重叠率为78.55%。针对不同风险要素的空间分异特征，提出了疫情防控的规划策略。研究结果能够准确划分城市空间的风险等级，为疫情防控的规划应对和公共活动安全提供科学依据。
