Abstract
The 2019 Coronavirus Disease (COVID-19), with the characteristics of rapid onset, strong infectivity, fast transmission and wide susceptibility, has quickly swept China since its appearance in Wuhan, Hubei province. COVID-19 spreads among people mainly by movement and close contact. Railway plays an important role in transport people national-wide as its essential role in public transportation, which conduced to the spreading of COVID-19 from Hubei province to other provinces in some sense. Inspired by this, this paper collected the data of Trains with Infectors (TwI) reported by the national health commission of the People’s Republic of China. Then the spreading of COVID-19 via railway network with the concept of complex network is analyzed. Results show that nodes with higher centrality tends to provide more TwI, and the closure of Wuhan railway station significantly prevents the spreading of COVID-19.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chinazzi, M., et al.: The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science 368(6489), 395–400 (2020)
Du, Z., et al.: Risk for transportation of coronavirus disease from Wuhan to other cities in China. Emerging Infect. Dis. 26(5), 1049 (2020)
Iacus, S.M., Natale, F., Vespe, M.: Flight restrictions from china during the COVID-2019 coronavirus outbreak. arXiv preprint arXiv:2003.03686 (2020)
Kraemer, M.U., et al.: The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 368(6490), 493–497 (2020)
Prem, K., et al.: The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health 5(5), 261–270 (2020)
Sohrabi, C., et al.: World health organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19). Int. J. Surg. 76, 71–76 (2020)
Surveillances, V.: The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19)-China, 2020. China CDC Weekly 2(8), 113–122 (2020)
Tian, H., et al.: An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 368(6491), 638–642 (2020)
Wells, C.R., et al.: Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak. Proc. Natl. Acad. Sci. 117(13), 7504–7509 (2020)
Zhao, S., et al.: The association between domestic train transportation and novel coronavirus (2019-nCoV) outbreak in china from 2019 to 2020: a data-driven correlational report. Travel Med. Infect. Dis. 33, 101568 (2020)
Zheng, R., Xu, Y., Wang, W., Ning, G., Bi, Y.: Spatial transmission of COVID-19 via public and private transportation in China. Travel Med. Infect. Dis. 34, 101626 (2020)
Acknowledgements
This work is supported by National Natural Science Foundation of China (No. U1834211 and No. 61925302).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wu, X., Yang, M., Wang, H., Dong, H., Lü, J., Song, H. (2021). Spreading Dynamics Analysis for Railway Networks. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_12
Download citation
DOI: https://doi.org/10.1007/978-981-16-5188-5_12
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-5187-8
Online ISBN: 978-981-16-5188-5
eBook Packages: Computer ScienceComputer Science (R0)