PUBLIC TRANSIT RIDERSHIP ANALYSIS DURING THE COVID-19 PANDEMIC

  1. Samira Ahangari
  2. Celeste Chavis
  3. Mansoureh Jeihani

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Abstract

This study investigates the effect of the coronavirus (COVID-19) pandemic on public transport ridership in Baltimore and nine other U.S. cities similar to Baltimore, in terms of population and service area, during the first five months of 2020. The analysis is based on ridership numbers, vehicle revenue hours, and vehicles operated in maximum service. A compliance analysis was done between 2020 and 2019, as well as a monthly analysis of 2020 by mode and type of services. In comparison to 2019, the ridership decreases from March, the start of the pandemic, while all ten cities experienced the most decrease in ridership in April.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.25.20219105: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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 10.1101/2020.10.25.20219105v1 on medRxiv