Evidence map›Paper›PMID 40177027›Full record

ArticleSSM - population health2025

Why gender and sex matter in infectious disease modelling: A conceptual framework.

Diane Auderset, Julien Riou, Carole Clair, Matthieu Perreau, Yolanda Mueller, Joëlle Schwarz

Abstract read
In one paragraph

Article in SSM - population health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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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

6 authors.

Diane AudersetFaculty of Health Sciences, Simon Fraser University, Burnaby, Canada.
Julien RiouDepartment of Epidemiology and Health Systems, Unisanté, Centre for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland.
Carole ClairGender and Health Unit, Department of Ambulatory Care, Unisanté, Centre for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland.
Matthieu PerreauService of Immunology and Allergy, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Yolanda MuellerDepartment of Family Medicine, Unisanté, Centre for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland.
Joëlle SchwarzGender and Health Unit, Department of Ambulatory Care, Unisanté, Centre for Primary Care and Public Health & University of Lausanne, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic underscored the differential impact of infectious diseases across population groups, with gender and sex identified as important dimensions influencing transmission and health outcomes. Sex-related biological factors, such as differences in immune response and comorbidities, contribute to men's heightened severity risks, while gender norms and roles influence exposure patterns, adherence to prevention measures, and healthcare access, influencing women's higher reported infection rates in certain contexts. Despite widely observed gender/sex disparities, infectious disease models frequently overlook gender and sex as key dimensions, leading to gaps in understanding and potential blind spots in public health interventions. This paper develops a conceptual framework based on the Susceptible-Exposed-Infectious-Recovered/Deceased (SEIR/D) compartmental model to map pathways through which gender and sex may influence susceptibility, exposure, transmission, recovery, and mortality. Using a narrative review of modelling, epidemiological, and clinical studies, this framework identifies and characterises the main social and biological mechanisms on this matter-including gendered occupational exposure, differential adherence to preventive measures, and disparities in healthcare-seeking behaviour-alongside sex-based differences in immune response and disease severity. The framework also examines potential gender-related variations in epidemiological surveillance data, highlighting disparities in testing uptake and hospitalisation referrals that could influence model outputs. By synthesising these insights, this paper provides a theoretical foundation for integrating gender and sex into infectious disease models. It advocates for interdisciplinary collaboration between modellers, social scientists, and clinicians to advance gender- and sex-sensitive modelling approaches. Accounting for gender and sex can enhance predictive accuracy, inform intervention strategies, and promote health equity in pandemic response.

Indexed as

COVID-19 transmission dynamicsGender disparities in health outcomesGender/sex-sensitive modellingInfectious disease modellingSEIRD compartmental modelSex-based differencesSocial epidemiology

Identifiers

PMID40177027
PMCPMC11964676

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.