Critical Mobility, a practical criterion and early indicator for regional COVID-19 resurgence

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

The sharp reduction of human mobility in March 2020, as observed by anonymized cellphone data, has played an important role in thwarting a runaway COVID-19 pandemic. As the world is reopening, the risks of new flare-ups are rising. We report a data-driven approach, grounded in strong correlation between mobility and growth in COVID-19 cases two weeks later, to establish a spatial-temporal model of “critical mobility” maps that separate relatively safe mobility levels from dangerous ones. The normalized difference between the current and critical mobility has predictive power for case trajectories during the “opening-up” phases. For instance, actual mobility has risen above critical mobility in many southern US counties by the end of May, foreshadowing the latest virus resurgence. Encouragingly, critical mobility has been rising throughout the USA, likely due to face mask-wearing and social distancing measures. However, critical mobility is still well below pre-COVID mobility levels in most of the country suggesting continued mobility-reduction is still necessary.

Article activity feed

  1. SciScore for 10.1101/2020.07.30.20163790: (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

    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.