Evidence map›Paper›PMID 40421615›Full record

ArticleInternational journal of epidemiology2025

How COVID-19 affected academic publishing: a 3-year study of 17 million research papers.

Matthew Whitaker, Sabrina Rodrigues, Graham Cooke, Bérangère Virlon, Christl A Donnelly, Helen Ward, Paul Elliott, Marc Chadeau-Hyam

Abstract read
In one paragraph

Article in International journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Matthew WhitakerSchool of Public Health, Imperial College London, London, UK.ORCID 0000-0003-1363-6537
Sabrina RodriguesSchool of Public Health, Imperial College London, London, UK.
Graham CookeImperial College Healthcare NHS Trust, London, UK.
Bérangère VirlonInstitut Pasteur, Université Paris Cité, Paris, France.
Christl A DonnellySchool of Public Health, Imperial College London, London, UK.
Helen WardSchool of Public Health, Imperial College London, London, UK.
Paul ElliottSchool of Public Health, Imperial College London, London, UK.ORCID 0000-0002-7511-5684
Marc Chadeau-HyamSchool of Public Health, Imperial College London, London, UK.ORCID 0000-0001-8341-5436

Funding

Department of Health and Social Care, EnglandEuropean CommissionHorizon 2020 874627
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic induced an unprecedented response from the scientific research community. Previous studies have described disruption of the norms of academic publishing during this time. This study uses an epidemiological statistical toolkit alongside machine-learning methods to investigate the functioning of the scientific information-generation and -consumption ecosystem throughout the pandemic.

methodsA dataset of 17 million scientific research papers that were published between January 2019 and December 2022 was analysed. Data on citations and Altmetrics were harvested, and topic modelling was applied to abstracts. COVID-19-related articles were identified from title text. We investigated publication dynamics, correlations between citation metrics and Altmetrics, rates of publication in preprints, and temporal trends in topics, and compared these metrics in COVID-19 papers vs non-COVID-19 papers.

resultsThroughout 2020-2, 3.7% of English-language research output was on the topic of COVID-19. Journal articles on COVID-19 were published at a consistent rate during this period, while preprints peaked in early 2020 and decreased thereafter. COVID-19 preprints had lower publication rates in the peer-reviewed literature than other preprints, particularly those that were preprinted during early 2020. COVID-19 research received significantly more media and social media attention than non-COVID-19 research, and preprints received more attention, on average, than journal articles, with attention peaking during the initial wave and subsequent peaks corresponding to the emergence of novel variants. COVID-19 articles exhibited a higher correlation between Altmetrics and citation metrics compared with non-COVID-19 publications, suggesting a strong alignment between scientific and public attention.

conclusionThis study provides a comprehensive description of the rapid expansion of COVID-19 research, revealing evolving research areas and waxing and waning public interest across different topics. Preprints played an important role in disseminating scientific findings, but the level of coverage of preprinted findings emphasizes the need for guidelines in handling preprint research in media, particularly during a pandemic.

Indexed as

Biomedical ResearchCOVID-19PublishingBibliometricsHumansPandemicsSARS-CoV-2AltmetricsbibliometricsCOVID-19pandemicspolicy

Identifiers

PMID40421615
PMCPMC12107239

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.