Impact of Different Transportation Modes on the Transmission of COVID-19: Correlation and Strategies from a Case Study in Wuhan, China

Int J Environ Res Public Health. 2022 Nov 25;19(23):15705. doi: 10.3390/ijerph192315705.

Abstract

Transportation is the main carrier of population movement, so it is significant to clarify how different transportation modes influence epidemic transmission. This paper verified the relationship between different levels of facilities and epidemic transmission by use of the K-means clustering method and the Mann-Whitney U test. Next, quantile regression and negative binomial regression were adopted to evaluate the relationship between transportation modes and transmission patterns. Finally, this paper proposed a control efficiency indicator to assess the differentiated strategies. The results indicated that the epidemic appeared 2-3 days earlier in cities with strong hubs, and the diagnoses were nearly fourfold than in other cities. In addition, air and road transportation were strongly associated with transmission speed, while railway and road transportation were more correlated with severity. A prevention strategy that considered transportation facility levels resulted in a reduction of the diagnoses of about 6%, for the same cost. The results of different strategies may provide valuable insights for cities to develop more efficient control measures and an orderly restoration of public transportation during the steady phase of the epidemic.

Keywords: control efficiency; negative binomial regression; quantile regression; transmission pattern; transportation modes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / epidemiology
  • China / epidemiology
  • Cities / epidemiology
  • Humans
  • Transportation
  • Transportation Facilities

Grants and funding

This research was funded by National Key Research and Development Program of China, grant number 2021YFB1600100, National Natural Science Foundation of China Civil Aviation Joint Key Project, grant number U2033203, National Natural Science Foundation of China, grant number 52272333, Postgraduate Research & Practice Innovation Program of NUAA, grant number xcxjh20210705 and the Postgraduate Research & Practice Innovation Program of NUAA, grant number xcxjh20220719.