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Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model

Author

Listed:
  • Cui, Hongjun
  • Xie, Jinping
  • Zhu, Minqing
  • Tian, Xiaoyong
  • Wan, Ce

Abstract

In the post-epidemic era, people’s lives are gradually returning to normal, and travel is gradually resuming. The safe evacuation of cross-regional travelers in railway station has also attracted more and more attention, especially the evacuation behavior of college students in railway station. In this paper, considering the pedestrian dynamics mechanism in the emergency evacuation process during the COVID-19 normalized epidemic prevention and control, an Agent-based social force model was established to simulate the activities of college students in railway station. Combined with the virus infection transmission model, Monte Carlo simulation was used to calculate the total exposure time and the number of high-risk exposed people in the railway station evacuation process. In addition, sensitivity analysis was conducted on the total exposure time and the number of high-risk exposed people under 180 combinations of the number of initial infections, social distance, and the proportion of people wearing masks incorrectly. The results show that with the increase of social distances, the total exposure time and the number of high-risk exposures do not always decrease, but increase in some cases. The presence or absence of obstacles in the evacuation scene has no significant difference in the effects on total exposure time and the number of high-risk exposures. During the evacuation behavior of college students in railway station, choosing the appropriate number of lines can effectively reduce the total exposure time and the number of high-risk exposures. Finally, some policy suggestions are proposed to reduce the risk of virus transmission in the railway station evacuation process, such as choosing dynamic and reasonable social distance and the number of queues, and reducing obstacles.

Suggested Citation

  • Cui, Hongjun & Xie, Jinping & Zhu, Minqing & Tian, Xiaoyong & Wan, Ce, 2022. "Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    • Handle: RePEc:eee:phsmap:v:608:y:2022:i:p1:s0378437122008421
    DOI: 10.1016/j.physa.2022.128284
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    References listed on IDEAS

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    1. Xiao, Yao & Yang, Mofeng & Zhu, Zheng & Yang, Hai & Zhang, Lei & Ghader, Sepehr, 2021. "Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach," Transport Policy, Elsevier, vol. 109(C), pages 12-23.
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    4. Qiancheng Xu & Mohcine Chraibi, 2020. "On the Effectiveness of the Measures in Supermarkets for Reducing Contact among Customers during COVID-19 Period," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
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    Cited by:

    1. Yaming Zhang & Jiaqi Zhang & Yaya Hamadou Koura & Changyuan Feng & Yanyuan Su & Wenjie Song & Linghao Kong, 2023. "Multiple Concurrent Causal Relationships and Multiple Governance Pathways for Non-Pharmaceutical Intervention Policies in Pandemics: A Fuzzy Set Qualitative Comparative Analysis Based on 102 Countries," IJERPH, MDPI, vol. 20(2), pages 1-16, January.
    2. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).

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