Evidence map›Paper›PMID 40628489›Full record

ArticleProceedings. Biological sciences2025

Twenty years of infectious disease dynamics research: gender and race imbalances in publication and citation practices.

Juliana C Taube, Alexes Merritt, Shweta Bansal

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Juliana C TaubeDepartment of Biology, Georgetown University, Washington, DC, USA.ORCID 0000-0002-0100-7648
Alexes MerrittDepartment of Biology, Georgetown University, Washington, DC, USA.ORCID 0000-0003-1835-2074
Shweta BansalDepartment of Biology, Georgetown University, Washington, DC, USA.ORCID 0000-0002-1740-5421

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Publication practices accumulate to affect credibility and career advancement. Understanding authorship and citation practices is critical to addressing inequities. While citation bias has been demonstrated in several fields, it remains uncharacterized in infectious disease dynamics (IDD), a quantitative, interdisciplinary domain highly visible during the COVID-19 pandemic. We analyse IDD articles and their bibliographies from 2000 to 2019 using machine-learning algorithms to infer the gender and race/ethnicity of each article's lead and senior authors. We examine authorship and citation patterns by gender and racial group across geographic scales, including characterizing the author composition of each article's bibliography relative to the field. Our analysis reveals persistent gender and race imbalances in IDD research. Man-authored and White-authored publications dominate the field, with little progress in racial diversification of US and UK publications over the last two decades. Woman-authored articles have the most representative citation practices but are undercited, especially when women are senior authors. In the USA and UK, most citations feature White lead and senior authors, even when citing articles have lead or senior authors of colour. These findings underscore the urgent need for more inclusive IDD research practices. We discuss possible mechanisms and solutions to create opportunities for researchers from underrepresented groups.

Indexed as

AuthorshipBibliometricsCommunicable DiseasesCOVID-19Racial GroupsFemaleHumansMaleSex FactorsUnited Statescitation analysisinfectious disease dynamicsscience of science

Identifiers

PMID40628489
PMCPMC12308323

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.