地铁乘客的病毒载量演化模型和仿真

doi:10.3976/j.issn.1002-4026.20230108

山东科学 ›› 2024, Vol. 37 ›› Issue (2): 97-103.doi: 10.3976/j.issn.1002-4026.20230108

地铁乘客的病毒载量演化模型和仿真

卢守峰¹^,²(), 黄志康¹^,², 赵红云³

1.南京工业大学交通运输工程学院,江苏南京 211816
2.江苏省交通基础设施安全保障技术工程研究中心,江苏南京 211816
3.岳阳市公安局交通警察支队,湖南岳阳 414021

收稿日期:2023-07-12 出版日期:2024-04-20 发布日期:2024-04-09
作者简介:卢守峰(1978—),男,教授,研究方向为智能交通。E-mail:itslu@njtech.edu.cn
基金资助:
国家自然科学基金项目(71071024)

The evolution model and simulation of the viral load of subway passengers

LU Shoufeng¹^,²(), HUANG Zhikang¹^,², ZHAO Hongyun³

1. Transportation Engineering College, Nanjing Tech University, Nanjing 211816, China
2. Jiangsu Province Engineering Research Center of Transportation Infrastructure Security Technology, Nanjing 211816, China
3. Traffic Police Detachment of Yueyang Public Security Bureau, Yueyang 414021, China

Received:2023-07-12 Online:2024-04-20 Published:2024-04-09

摘要/Abstract

摘要：

为了微观刻画地铁乘客的病毒传播,构建了吸入病毒概率与社交距离之间的函数关系,建立了病毒载量增加量和减少量的计算公式,在此基础上建立了病毒载量演化方程,其中防疫措施的效果以归一化的参数描述。通过Anylogic软件的二次开发接口,对每个乘客的病毒载量进行编程,刻画每个乘客在感染前和感染后两个阶段的病毒载量变化。仿真初始时刻设定10%的乘客被病毒感染,包括普通感染者和超级感染者。对不同乘客数量条件下的病毒演化进行仿真,分为有管控和无管控两种场景。仿真结果表明:随着乘车人数的增多,乘客密度增大,病毒传播增强,个体病毒载量增加较快;对病毒载量大于1 000的乘客进行管控,禁止其乘车,可将所有乘客的病毒载量降低一个数量级。

关键词: 城市交通, 地铁乘客, 病毒载量, 疫情管控, 演化模型, Anylogic仿真

Abstract:

A functional relationship was constructed between the probability of inhaling viruses and social distance to characterize the viral transmission of subway passengers at the microscopic level. Formulas for calculating the increase and decrease of viral load were constructed based on establishing the viral load evolution equation. Normalized parameters were used within this equation to describe the effect of pandemic prevention measures. The viral load of each passenger was programmed through the Anylogic software’s secondary development interface to characterize the viral load change at the pre- and post-infection phases. In the initial simulation settings, 10% of the passengers were infected with the virus, including ordinary carriers and supercarriers. The evolution of the virus under different passenger number conditions within subway carriages was simulated, which was categorized into with-control and without-control scenarios. The simulation results showed the following: as the number of passengers increases, the passenger density increases, the virus transmission increases, and the individual viral load increases rapidly. Isolating passengers with a viral load greater than a threshold of 1 000 and prohibiting them from taking the subway can reduce the viral load of all passengers by an order of magnitude.

Key words: urban transportation, subway passengers, viral load, pandemic control, evolutionary model, Anylogic simulation

中图分类号:

卢守峰, 黄志康, 赵红云. 地铁乘客的病毒载量演化模型和仿真[J]. 山东科学, 2024, 37(2): 97-103.

LU Shoufeng, HUANG Zhikang, ZHAO Hongyun. The evolution model and simulation of the viral load of subway passengers[J]. Shandong Science, 2024, 37(2): 97-103.

图/表 5

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地铁乘客的病毒载量演化模型和仿真

The evolution model and simulation of the viral load of subway passengers

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