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

COVID-19 authorship bibliometrics citations productivity

Journal

Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528

Informations de publication

Date de publication:
Sep 2021
Historique:
received: 17 03 2021
accepted: 02 09 2021
entrez: 16 9 2021
pubmed: 17 9 2021
medline: 17 9 2021
Statut: epublish

Résumé

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 (

Identifiants

pubmed: 34527271
doi: 10.1098/rsos.210389
pii: rsos210389
pmc: PMC8422596
doi:

Banques de données

figshare
['10.6084/m9.figshare.c.5604743']

Types de publication

Journal Article

Langues

eng

Pagination

210389

Informations de copyright

© 2021 The Authors.

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Auteurs

John P A Ioannidis (JPA)

Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.
Meta-Research Innovation Center Berlin (METRIC-B), QUEST, Berlin Institute of Health, Berlin, Germany.

Maia Salholz-Hillel (M)

Meta-Research Innovation Center Berlin (METRIC-B), QUEST, Berlin Institute of Health, Berlin, Germany.

Kevin W Boyack (KW)

SciTech Strategies, Inc., Albuquerque, NM, USA.

Jeroen Baas (J)

Research Intelligence, Elsevier B.V., Amsterdam, The Netherlands.

Classifications MeSH