基于出行行为模型的出行感染风险评估 ——以新冠肺炎疫情期间江苏省地区为例

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (6): 63-70.

基于出行行为模型的出行感染风险评估 ——以新冠肺炎疫情期间江苏省地区为例

曹奇^{1a, 1b, 1c}，任刚^{*1a, 1b, 1c}，李大韦^{1a, 1b, 1c}，朱茂莹²，马景峰^{1a, 1b, 1c}，宋建华^{1a, 1b, 1c}，朱玉霖^{1a, 1b, 1c}，何煜洪^{1a, 1b, 1c}

1. 东南大学 a. 江苏省城市智能交通重点实验室，b. 现代城市交通技术江苏高校协同创新中心， c. 交通学院，南京 211189；2. 南京大学政府管理学院，南京 210023

收稿日期:2020-04-15 修回日期:2020-06-24 出版日期:2020-12-25 发布日期:2020-12-25
作者简介:曹奇(1992-)，男，江苏徐州人，博士生.
基金资助:
国家重点研发计划项目/National Key Research and Development Program of China (2019YFB1600200).

Assessment of Infection Risk Based on Travel Behavior Analysis ——Example of Jiangsu Province Travel during COVID-19

CAO Qi^{1a, 1b, 1c} , REN Gang^{1a, 1b, 1c} , LI Da-wei^{1a, 1b, 1c} , ZHU Mao-ying² , MA Jing-feng^{1a, 1b, 1c}, SONG Jian-hua^{1a, 1b, 1c} , ZHU Yu-lin^{1a, 1b, 1c} , HE Yu-hong^{1a, 1b, 1c}

1a. Jiangsu Key Laboratory of Urban ITS, 1b. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, 1c. School of Transportation, Southeast University, Nanjing 211189, China; 2. School of Government, Nanjing University, Nanjing 210023, China

Received:2020-04-15 Revised:2020-06-24 Online:2020-12-25 Published:2020-12-25

摘要/Abstract

摘要：

为准确评估新冠肺炎疫情期间的出行感染风险，在对出行行为进行全出行链建模基础上提出出行风险评估模型.基于江苏省确诊病例流行病学调查报告和线上问卷调查数据，分别对病毒携带者和普通出行者出行行为模型进行参数标定，对比分析病毒携带者和普通出行者出行行为的异同.进一步对疫情期间不同出行方式和出行活动进行感染风险评估. 得到结论：交通管制措施可有效降低出行感染风险，就医出行风险明显高于其他出行活动，差旅在疫情传播初期风险较高，非机动车出行风险相对较低.

关键词: 交通工程, 出行风险评估, 出行行为模型, 新冠肺炎疫情

Abstract:

In order to correctly evaluate the travel infection risks during the COVID- 19 pandemic, this study proposed an infection risk assessment model based on the travel behavior analysis. Using the epidemiological survey data and online questionnaire data in Jiangsu, China this study developed and calibrated the travel behavior models for virus carriers and ordinary individuals. The travel behaviors of virus carriers and ordinary individuals were also compared. The infection risks were evaluated for different travel modes and travel activities. The results indicate that: (1) implementing strict traffic control measures significantly reduces the infection risk; (2) the infection risk of medical treatment travel activities is significantly higher than other travel activities; (3) business or leisure travel activities expose to a higher infection risk in the early stages of the pandemic; (4) the risk of nonmotor vehicle travel is relatively low.

Key words: traffic engineering, risk assessment, travel behavior model, COVID-19

中图分类号:

U491

曹奇，任刚，李大韦，朱茂莹，马景峰，宋建华，朱玉霖，何煜洪. 基于出行行为模型的出行感染风险评估 ——以新冠肺炎疫情期间江苏省地区为例[J]. 交通运输系统工程与信息, 2020, 20(6): 63-70.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract20149.shtml

http://www.tseit.org.cn/CN/Y2020/V20/I6/63

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