Abstract: The global coronavirus pandemic has severely tested the ability of cities to respond to major public health emergencies. COVID-19（Corona Virus Disease 2019，COVID-19） is an infectious disease spread by air and contact, with human-to-human transmissions. Humans are both the cause and the recipients of this disaster. With the basic properties of population gathering and movement, cities have become hotbeds for the spread of infectious diseases. The TOD（transit-oriented development，TOD） mode of urban rail transit enables the large-scale movement and public gathering of the urban population through mass commuting and large-scale services along and in station areas. Theoretically, this may cause large-scaled spreading of infectious diseases from station areas to more extensive areas along the rail line. However, an empirical study of the actual influences of TOD on infectious disease transmission based on prevention and control is needed. This can provide information for the tracking and spreading spatial patterns of infectious diseases under the effects of prevention and control.
　　Firstly, a reasonable hypothesis that TOD affects the large-scaled transmission of infectious diseases was proposed based on the interaction mechanism between population activity and infectious disease transmission. A variable system of influences of TOD on infectious disease transmission was designed. Secondly, a statistical analysis of the influences of TOD on the risk of COVID-19 transmission in streets of main urban areas in Beijing based on the urban prevention and control strategies in 2020 was carried out. Finally, it was concluded that TOD influenced spatial characteristics of infectious disease transmission. Realistic scenarios and theoretical hypotheses were compared. Results provided references for the study of urban-infectious disease transmissions under based on prevention and control strategies from the perspective of TOD.
　　Specifically, an ordered logistic regression analysis was conducted on 133 blocks in the main urban area of Beijing. The scale of confirmed cases was used as the dependent variable, the TOD coverage rate of rail transit was used as the independent variable, and the conditions related to the transmission and prevention of infectious diseases and the distance to the epidemic source were used as the control variable. Based on infectious disease prevention and control strategies, the rail transit TOD failed to significantly increase the risk of infectious disease transmission in streets along rail lines. Instead, the risk of infectious disease transmission in streets with fewer stations was higher. Moreover, with the exception of resident population size, imbalanced resource conditions of blocks did not cause significant differences in the distribution of infectious disease transmission risk. A Spearman correlation analysis on the scale of confirmed cases, as well as flow and aggregation variables of rail transit TOD, was further carried out. Here, rail transit transfer and regional stations failed to significantly increase the risk of infectious disease transmission in streets along rail lines, but had greater influences on streets further away from the rail radius. 
Research results on the COVID-19 epidemic in Beijing's Xinfadi market in 2020 are a microcosm of the comprehensive effect of a virus in development and prevention and control measures in accordance with local conditions at that moment. These were not correlated to time or space. However, this information can provide useful references for the expansion and deepening of research on the city-infectious disease transmission from the perspective of TOD development and construction in China. On the one hand, the analysis results reflected the effectiveness of epidemic prevention and control measures in typical cities in China represented by Beijing at the time. On the other hand, the analysis results highlighted the challenges of prevention and control in areas which are further away from the rail radius and have internal circulation of population activities.

Key words: urban rail transit, TOD, prevention and control, infectious disease transmission

摘要： 城市轨道交通TOD模式通过沿线大运量通勤和站区规模化服务，承载了人口的大规模流动和公共性聚集，理论上会以站区为核心，造成从沿线地区至更广泛辐射地区的传染病传播。然而，以2020年北京新发地新冠肺炎疫情为例，对北京主城区133个街道做有序Logistic回归分析发现，在传染病防控治理背景下，轨道交通TOD没有显著引起沿线街道传染病传播风险增加。其中，街道之间除常住人口规模外，多项资源条件的不平衡没有导致传染病传播风险分布的显著差异。进一步通过Spearman相关性分析发现，换乘站和区域站对传染病传播风险的升级影响仅表现在更远离轨道辐射的街道。分析结果一方面反映出彼时我国以北京为典型的城市疫情防控治理效果，另一方面也凸显了远离轨道辐射、人口活动具有内循环特征地区的防控挑战。

关键词: 城市轨道交通, TOD, 防控治理, 传染病传播