The evolving role of preprints in the dissemination of COVID-19 research and their impact on the science communication landscape

  1. Nicholas Fraser
  2. Liam Brierley
  3. Gautam Dey
  4. Jessica K. Polka
  5. Máté Pálfy
  6. Federico Nanni
  7. Jonathon Alexis Coates

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Abstract

The world continues to face a life-threatening viral pandemic. The virus underlying the Coronavirus Disease 2019 (COVID-19), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has caused over 98 million confirmed cases and 2.2 million deaths since January 2020. Although the most recent respiratory viral pandemic swept the globe only a decade ago, the way science operates and responds to current events has experienced a cultural shift in the interim. The scientific community has responded rapidly to the COVID-19 pandemic, releasing over 125,000 COVID-19–related scientific articles within 10 months of the first confirmed case, of which more than 30,000 were hosted by preprint servers. We focused our analysis on bioRxiv and medRxiv, 2 growing preprint servers for biomedical research, investigating the attributes of COVID-19 preprints, their access and usage rates, as well as characteristics of their propagation on online platforms. Our data provide evidence for increased scientific and public engagement with preprints related to COVID-19 (COVID-19 preprints are accessed more, cited more, and shared more on various online platforms than non-COVID-19 preprints), as well as changes in the use of preprints by journalists and policymakers. We also find evidence for changes in preprinting and publishing behaviour: COVID-19 preprints are shorter and reviewed faster. Our results highlight the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science and the impact of the pandemic on the scientific communication landscape.

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  1. Version published to 10.1371/journal.pbio.3000959
  2. ScreenIT

    SciScore for 10.1101/2020.05.22.111294: (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

    Software and Algorithms
    SentencesResources
    Screening time for bioRxiv and medRxiv: To calculate screening time, we followed the method outlined by Steve Royle [57].
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)

    Results from OddPub: Thank you for sharing your code and data.

    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.

  3. Version published to 10.1101/2020.05.22.111294v3 on bioRxiv
  5. Version published to 10.1101/2020.05.22.111294v2 on bioRxiv
  6. Rapid Reviews Infectious Diseases

    Noah Haber

    Review 1: "Preprinting a pandemic: the role of preprints in the COVID-19 pandemic"

    This study proves that COVID-19 has led to the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science. Findings are robust and informative, though there are some errors and misinterpretations.

  7. Rapid Reviews Infectious Diseases

    Siran He, Emily Smith

    Review 2: "Preprinting a pandemic: the role of preprints in the COVID-19 pandemic"

    This study proves that COVID-19 has led to the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science. Findings are robust and informative, though there are some errors and misinterpretations.

  8. ScreenIT

    SciScore for 10.1101/2020.05.22.111294: (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

    Antibodies
    SentencesResources
    The most tweeted COVID-19 preprint ( 29,984 tweets ) was a study investigating antibody seroprevalence in California [ 30] , whilst the second most tweeted COVID-19 preprint was a widely criticised ( and later withdrawn ) study linking the SARS-CoV-2 spike protein to HIV-1 glycoproteins .
    HIV-1 glycoproteins .
    suggested: None
    Software and Algorithms
    SentencesResources
    Methods Preprint Metadata for bioRxiv and medRxiv We retrieved basic preprint metadata ( DOIs , titles , abstracts , author names , corresponding author name and institution , dates , versions , licenses , categories and published article links ) for bioRxiv and medRxiv preprints via the bioRxiv Application Programming Interface ( API; https://api.biorxiv.org).
    bioRxiv
    suggested: (bioRxiv, SCR_003933)

    Results from OddPub: Thank you for sharing your code and data.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  9. Version published to 10.1101/2020.05.22.111294v1 on bioRxiv