Evidence map›Paper›PMID 42598046›Full record

ReviewDialogues in health2026

Gender-responsive infectious disease models: Guidelines and systematic scoping review.

Alisa Hamilton, Indira Prihartono, Yamato Okura, Naomi Rankin, Samee Saiyed, Jeremy Ratcliff, Ayo Oladimeji, Tak Igusa, Lauren Gardner, Rosemary Morgan

Abstract readReview
In one paragraph

Review in Dialogues in health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Alisa HamiltonWhiting School of Engineering, Johns Hopkins University, USA.
Indira PrihartonoBloomberg School of Public Health, Johns Hopkins University, USA.
Yamato OkuraWhiting School of Engineering, Johns Hopkins University, USA.
Naomi RankinWhiting School of Engineering, Johns Hopkins University, USA.
Samee SaiyedWhiting School of Engineering, Johns Hopkins University, USA.
Jeremy RatcliffWhiting School of Engineering, Johns Hopkins University, USA.
Ayo OladimejiWhiting School of Engineering, Johns Hopkins University, USA.
Tak IgusaWhiting School of Engineering, Johns Hopkins University, USA.
Lauren GardnerWhiting School of Engineering, Johns Hopkins University, USA.
Rosemary MorganBloomberg School of Public Health, Johns Hopkins University, USA.

Funding

Bill & Melinda Gates Foundation INV-032701
6 · The paper itself

Abstract

Background: Sex and gender influence infectious disease outcomes through biological and social mechanisms. Gender norms, roles, and behaviors affect exposure, care-seeking, and service access, yet many infectious disease models overlook these factors. Methods: To provide guidance to researchers considering sex/gender in epidemiological models, we propose structured guidelines for developing gender-responsive infectious disease models, adapted from an established monitoring and evaluation framework. Recommendations include: 1) using sex/gender-disaggregated or sex/gender-specific populations; 2) incorporating an additional social stratifier (e.g., age, race/ethnicity); 3) maintaining stratification in results; 4) addressing the needs, rights, and preferences of gender groups; and 5) grounding models in context with participation from target groups. To provide examples, we conducted a scoping review using these criteria, drawing from HIV, COVID-19, and malaria literature. Findings: Of 7303 studies screened, 45 met inclusion criteria. Most modeled HIV (96%), used compartmental (73%) or agent-based (22%) approaches, and included sexual orientation or occupation as an additional stratifier. Studies contextualized their models by discussing local healthcare systems, unequal access to care, stigma, gender norms in partnership dynamics, and occupational risk. Interpretation: Gender-responsive modeling is feasible but uncommon beyond sexually transmitted infections. Applying intersectional, context-specific approaches can reveal disparities and inform equitable, efficient interventions. These guidelines can be adapted to address other health disparities.

Indexed as

COVID-19Gender disparitiesHealth equityHIVInfectious disease modelingMalariaMathematical modeling

Identifiers

PMID42598046
PMCPMC13471233

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.