Initial Simulation of SARS-CoV2 Spread and Intervention Effects in the Continental US

  1. Sen Pei
  2. Jeffrey Shaman

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Abstract

Here we use a metapopulation model applied at county resolution to simulate the spread and growth of COVID-19 incidence in the continental United States. We calibrate the model against county-level incidence data collected between February 21, 2020 and March 13, 2020, and estimate epidemiological parameters including the fraction of undocumented infections and their contagiousness 1 . Using the calibrated model, we project the outbreak in the continental US for 180 days after March 13, 2020, and evaluate the effects of social distancing and travel restrictions on the outbreak.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.21.20040303: (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.
    • 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 10.1101/2020.03.21.20040303v2 on medRxiv
  3. Version published to 10.1101/2020.03.21.20040303v1 on medRxiv