Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (1): 141-149.doi: 10.13229/j.cnki.jdxbgxb20210587

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Modeling urban bus transit spreading the epidemic under public health emergencies

Shao-jie WU1,2,3(),Jian SUN1,2,3()   

  1. 1.College of Transportation Engineering，Chang'an University，Xi'an 710021，China
    2.College of Future Transportation，Chang'an University，Xi'an 710021，China
    3.Smart City and Intelligent Transportation Interdisciplinary Center，Chang'an University，Xi'an 710021，China
  • Received:2021-06-26 Online:2023-01-01 Published:2023-07-23
  • Contact: Jian SUN E-mail:wushaojie@chd.edu.cn;jiansun@chd.edu.cn

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Abstract:

To reveal the influence of urban public transportation on the dispersion of COVID-19 within the city， an F-SEIR model considering migrants is established to analyze the impact of inter-regional population movement on the spread of the epidemic. The epidemic transmission characteristics within enclosed public buses were considered， on which， an COVID-19 influenced model of urban public transportation communication was established. Using IC card data and GPS data of public transportation in Wuhan， the empirical case study was simulated with each of the 160 towns in Wuhan as the analysis units. The results demonstrated that under the influence of public transportation， the spread of urban epidemic is accelerated and the phenomenon of "flying point transmission" appears in many towns， and the number of infected people attains 70 446. Timely countermeasures to suspend public transportation have successfully reduced the number of infected persons by 18.64% to 28.34%， and the earlier the measures are taken， the larger total number of infected persons are reduced. The model accurately fits the evolutionary trends of COVID-19. By comparing the simulation results from different dates after the shutdown of publication transportation service on Jan. 23， 2020， the goodness-of-fit between the fitted data and the official epidemic data attains as high as 0.9675. The model is helpful to understand the impact of public transportation on the spread of the epidemic within cities， which may further provide theoretical and decision-making guidance for risk evaluation and policy stipulating during the different stages of other major public health events.

Key words: major public health events, COVID-19, urban transport, SEIR model, bus IC card data

CLC Number: 

  • U121

Fig.1

Schematic diagram of F-SEIR model"

Fig.2

Schematic diagram of COVID-19 spreading model with urban transportation system"

Fig.3

Density distribution of bus stops by town in Wuhan， China"

Fig.4

Passenger travel chain situations"

Fig.5

Model implementation process"

Fig.6

Trend of infected people with different infection rates"

Fig.7

Trend of infected and cured people under extreme condition"

Fig.8

Spatial distribution of infected persons by town in Wuhan， China"

Fig.9

Trend of infected persons under three different conditions"

Table 1

Part of the simulation and official released data"

日期仿真感染人数官方公布感染数相对误差/%
2月12日41 35132 99425.33
2月15日44 73739 46213.37
2月18日47 23944 4126.36
2月21日48 85345 6606.99
2月24日49 92247 0716.05
2月27日50 61948 1375.16
3月01日50 94049 3153.30
3月04日51 11249 6712.90
3月07日51 17049 9122.52
3月10日51 18649 9782.42
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