Universities and COVID-19 Growth at the Start of the 2020 Academic Year

  1. Mike Penuliar
  2. Candice Clark
  3. Debbie Curti
  4. Cathy Hudson
  5. Billy Philips

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Abstract

The global pandemic of 2020 caused by the novel coronavirus of 2019 (COVID-19) has uprooted the education system of the United States. As American colleges and universities try to resume regular instruction for the 2020-2021 academic year, outbreaks have begun to emerge and university towns across the country are now virus hotspots. The current paper provides two studies. First, the current work investigates how the growth of COVID-19 compares in areas with large universities against those without. Results showed markedly increase case growth in counties with large universities at the start of the fall 2020 semester. Secondly, this work provides a highly accessible and modifiable epidemiological tool known as a susceptible-infected-removed model for educational administrators that will allow users to see the impact of COVID-19 historically and predictively. The results of an exemplar model using a large public research university, Texas Tech University, are discussed.

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  1. ScreenIT

    SciScore for 10.1101/2020.11.25.20238899: (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: Thank you for sharing your code.

    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.
    • No funding statement was detected.
    • 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 10.1101/2020.11.25.20238899 on medRxiv