Direct Measurement of Rates of Asymptomatic Infection and Clinical Care-Seeking for Seasonal Coronavirus

  1. Jeffrey Shaman
  2. Marta Galanti

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Abstract

The pandemic potential of the novel coronavirus (nCoV) that emerged in Wuhan, China, during December 2019 is strongly tied to the number and contagiousness of undocumented human infections. Here we present findings from a proactive longitudinal sampling study of acute viral respiratory infections that documents rates of asymptomatic infection and clinical care seeking for seasonal coronavirus. We find that the majority of infections are asymptomatic by most symptom definitions and that only 4% of individuals experiencing a seasonal coronavirus infection episode sought medical care for their symptoms. These numbers indicate that a very high percentage of seasonal coronavirus infections are undocumented and provide a reference for understanding the spread of the emergent nCoV.

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  1. ScreenIT

    SciScore for 10.1101/2020.01.30.20019612: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Participants (or their guardians, if minors) provided informed consent after reading a detailed description of the study (CUMC IRB
    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 10.1101/2020.01.30.20019612v1 on medRxiv