Synchronized travel restrictions across cities can be effective in COVID-19 control

  1. Haiyan Liu
  2. Xuemei Bai
  3. Huanfeng Shen
  4. Xiaoping Pang
  5. Zeyu Liang
  6. Yue Liu

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The COVID-19 outbreak is under control in China. Mobility interventions, including both the Wuhan lockdown and travel restrictions in other cities, have been undertaken in China to mitigate the epidemic. However, the impact of mobility restrictions in cites outside Wuhan has not been systematically analyzed. Here we ascertain the relationships between all mobility patterns and the epidemic trajectory in Chinese cities outside Hubei Province, and we estimate the impact of local travel restrictions. We estimate local inter-city travel bans averted 22.4% (95% PI: 16.8–27.9%) more infections in the two weeks after the Wuhan lockdown, while local intra-city travel prevented 32.5% (95% PI: 18.9–46.1%) more infections in the third and fourth weeks. More synchronized implementation of mobility interventions would further decrease the number of confirmed cases in the first two weeks by 15.7% (95% PI:15.4–16.0%). This study shows synchronized travel restrictions across cities can be effective in COVID-19 control.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.02.20050781: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical decisions were all made at a 5% level of significance using SPSS software.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.04.02.20050781v2 on medRxiv
  3. Version published to 10.1101/2020.04.02.20050781v1 on medRxiv