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Exploring the roles of high-speed train, air and coach services in the spread of COVID-19 in China

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  • Zhang, Yahua
  • Zhang, Anming
  • Wang, Jiaoe

Abstract

To understand the roles of different transport modes in the spread of COVID-19 pandemic across Chinese cities, this paper looks at the factors influencing the number of imported cases from Wuhan and the spread speed and pattern of the pandemic. We find that frequencies of air flights and high-speed train (HST) services out of Wuhan are significantly associated with the number of COVID-19 cases in the destination cities. The presence of an airport or HST station at a city is significantly related to the speed of the pandemic spread, but its link with the total number of confirmed cases is weak. The farther the distance from Wuhan, the lower number of cases in a city and the slower the dissemination of the pandemic. The longitude and latitude coordinates do not have a significant relationship with the number of total cases but can increase the speed of the COVID-19 spread. Specifically, cities in the higher longitudinal region tended to record a COVID-19 case earlier than their counterparties in the west. Cities in the north were more likely to report the first case later than those in the south. The pandemic may emerge in large cities earlier than in small cities as GDP is a factor positively associated with the spread speed.

Suggested Citation

  • Zhang, Yahua & Zhang, Anming & Wang, Jiaoe, 2020. "Exploring the roles of high-speed train, air and coach services in the spread of COVID-19 in China," Transport Policy, Elsevier, vol. 94(C), pages 34-42.
  • Handle: RePEc:eee:trapol:v:94:y:2020:i:c:p:34-42
    DOI: 10.1016/j.tranpol.2020.05.012
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    References listed on IDEAS

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    1. Wang, Kun & Xia, Wenyi & Zhang, Anming, 2017. "Should China further expand its high-speed rail network? Consider the low-cost carrier factor," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 105-120.
    2. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    3. Zhu, Zhenran & Zhang, Anming & Zhang, Yahua, 2018. "Connectivity of intercity passenger transportation in China: A multi-modal and network approach," Journal of Transport Geography, Elsevier, vol. 71(C), pages 263-276.
    4. Zhang, Anming & Wan, Yulai & Yang, Hangjun, 2019. "Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research," Transport Policy, Elsevier, vol. 81(C), pages 1-19.
    5. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    6. van Bergeijk,Peter A. G. & Brakman,Steven (ed.), 2010. "The Gravity Model in International Trade," Cambridge Books, Cambridge University Press, number 9780521196154.
    7. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275.
    9. Elhanan Helpman & Marc Melitz & Yona Rubinstein, 2008. "Estimating Trade Flows: Trading Partners and Trading Volumes," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 441-487.
    10. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    11. Wang, Jiaoe & Mo, Huihui & Wang, Fahui & Jin, Fengjun, 2011. "Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 712-721.
    12. Wang, Jiaoe & Du, Delin & Huang, Jie, 2020. "Inter-city connections in China: High-speed train vs. inter-city coach," Journal of Transport Geography, Elsevier, vol. 82(C).
    13. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
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