Skip to main navigation Skip to search Skip to main content

Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China

  • Xiao-Ke Xu (Co-first Author)
  • , Xiao Fan Liu (Co-first Author)
  • , Lin Wang (Co-first Author)
  • , Ye Wu
  • , Xin Lu
  • , Xianwen Wang
  • , Sen Pei*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

64 Downloads (CityUHK Scholars)

Abstract

The spatial spread of COVID-19 during early 2020 in China was primarily driven by outbound travelers leaving the epicenter, Wuhan, Hubei province. Existing studies focus on the influence of aggregated out-bound population flows originating from Wuhan; however, the impacts of different modes of transportation and the network structure of transportation systems on the early spread of COVID-19 in China are not well understood. Here, we assess the roles of the road, railway, and air transportation networks in driving the spatial spread of COVID-19 in China. We find that the short-range spread within Hubei province was dominated by ground traffic, notably, the railway transportation. In contrast, long-range spread to cities in other provinces was mediated by multiple factors, including a higher risk of case importation associated with air transportation and a larger outbreak size in hub cities located at the center of transportation networks. We further show that, although the dissemination of SARS-CoV-2 across countries and continents is determined by the worldwide air transportation network, the early geographic dispersal of COVID-19 within China is better predicted by the railway traffic. Given the recent emergence of multiple more transmissible variants of SARS-CoV-2, our findings can support a better assessment of the spread risk of those variants and improve future pandemic preparedness and responses.

Original languageEnglish
Pages (from-to)305-310
Number of pages6
JournalFundamental Research
Volume3
Issue number2
Online published22 Apr 2022
DOIs
Publication statusPublished - Mar 2023

Funding

This work was supported by the National Natural Science Foundation of China [ 61773091 and 62173065 to X.-K. X., 11975025 to L. W., 11875005 to Y. W., 72025405 and 82041020 to X. L., 71974029 to X. W.]; the Grand Challenges ICODA pilot initiative, delivered by Health Data Research UK and funded by the Bill & Melinda Gates Foundation and the Minderoo Foundation [to X.F. L.]; US CDC Grant 20U01CK000592 [to S.P.]; and US CDC and CSTE Grant NU38OT00297 [to S.P.].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • COVID-19
  • Human mobility
  • Transportation networks
  • Spatial spread
  • Complex network

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

Fingerprint

Dive into the research topics of 'Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China'. Together they form a unique fingerprint.

Cite this