Exploring the Temporal Dynamics of County-Level Vulnerability Factors on COVID-19 Outcomes

  1. Jing Zhang
  2. Daesung Choi
  3. Shivani A Patel
  4. Joyce C. Ho

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Abstract

As the outbreak of COVID-19 has become a severe worldwide pandemic, every country fights against the spread of this deadly disease with incredible efforts. There are numerous researches along with every conceivable dimension for COVID-19. Among these researches, different demographic and contextual factors of populations and communities also play an essential role in providing more information for decision-makers. This paper mainly utilizes existing data on county contextual factors at the United States county-level to develop a model that can capture the dynamic trajectory of COVID-19 (i.e., cases) and its impacts across the United States. Moreover, our methods applied to contextual data achieves better results compared with existing measures of vulnerability.

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    SciScore for 10.1101/2021.11.24.21266757: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2021.11.24.21266757v1 on medRxiv