The rapid, massive growth of COVID-19 authors in the scientific literature

  1. John P. A. Ioannidis
  2. Maia Salholz-Hillel
  3. Kevin W. Boyack
  4. Jeroen Baas

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

We examined the extent to which the scientific workforce in different fields was engaged in publishing COVID-19-related papers. According to Scopus (data cut, 1 August 2021), 210 183 COVID-19-related publications included 720 801 unique authors, of which 360 005 authors had published at least five full papers in their career and 23 520 authors were at the top 2% of their scientific subfield based on a career-long composite citation indicator. The growth of COVID-19 authors was far more rapid and massive compared with cohorts of authors historically publishing on H1N1, Zika, Ebola, HIV/AIDS and tuberculosis. All 174 scientific subfields had some specialists who had published on COVID-19. In 109 of the 174 subfields of science, at least one in 10 active, influential (top 2% composite citation indicator) authors in the subfield had authored something on COVID-19. Fifty-three hyper-prolific authors had already at least 60 (and up to 227) COVID-19 publications each. Among the 300 authors with the highest composite citation indicator for their COVID-19 publications, most common countries were USA ( n = 67), China ( n = 52), UK ( n = 32) and Italy ( n = 18). The rapid and massive involvement of the scientific workforce in COVID-19-related work is unprecedented and creates opportunities and challenges. There is evidence for hyper-prolific productivity.

Article activity feed

  1. Version published to 10.1098/rsos.210389
  2. Version published to 10.1101/2020.12.15.422900v3 on bioRxiv
  3. Version published to 10.1101/2020.12.15.422900v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.12.15.422900: (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: 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: We detected the following sentences addressing limitations in the study:
    Certain limitations should be discussed. First, current Scopus data have high precision and recall (98.1% and 94.4%, respectively),1 but some authors may be split in two or more records and some ID records may include papers from two or more authors. These errors may affect single authors but are unlikely to affect the overall picture obtained in these analyses. Second, field and subfield classification follows a well-known established method, though published items are not precisely categorizable in scientific fields. Third, data on citation impact of COVID-19 authors are too early to appraise with confidence, and the ranking of specific scientists is highly tenuous and can quickly change with relatively small changes in citation counts. The bigger picture of author characteristics rather than specific names should be the focus of these data. Fourth, since many COVID-19 accepted papers and preprints are not yet indexed in Scopus, fields with slower publication and indexing may be relatively under-represented in the analyses. As the pandemic matures, the science of COVID-19 should also mature. Important remaining questions can be raised about the extent and duration of this “covidization” of research. Will scientists continue to flock from different disciplines into COVID-19 research? What consequences might this have for other areas of important investigation – could non-COVID-19 topics be unfairly neglected? Is the response proportional to the magnitude of the crisis? What ...

    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.

  5. Version published to 10.1101/2020.12.15.422900v1 on bioRxiv