Evidence map›Paper›PMID 39828430›Full record

ArticleBMJ global health2025

Beyond COVID-19, the case for collecting, analysing and using sex-disaggregated data and gendered data to inform outbreak response: a scoping review.

McKinzie Gales, Emelie Love Yonally Phillips, Leah Zilversmit Pao, Christine Dubray, Clara Rodriguez Ribas Elizalde, Shirin Heidari, Marie-Amelie Degail, Marie Meudec, M Ruby Siddiqui, Simone E Carter

Abstract readScoping Review
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

McKinzie GalesGlobal Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Emelie Love Yonally PhillipsEpidemiology Intervention and Training Department, Epicentre, Paris, France emelie.yp@gmail.com.ORCID http://orcid.org/0009-0000-7095-0851
Leah Zilversmit PaoCenters for Disease Control and Prevention, Atlanta, Georgia, USA.
Christine DubrayCenters for Disease Control and Prevention, Atlanta, Georgia, USA.
Clara Rodriguez Ribas ElizaldeWorld Health Organization, Geneva, GE, Switzerland.ORCID http://orcid.org/0000-0002-9832-4796
Shirin HeidariGraduate Institute of International and Development Studies, Geneve, GE, Switzerland.
Marie-Amelie DegailHealth Emergencies Programme, World Health Organization, Geneve, GE, Switzerland.ORCID http://orcid.org/0000-0002-5522-7515
Marie MeudecPublic Health, Institute of Tropical Medicine, Antwerpen, Antwerpen, Belgium.ORCID http://orcid.org/0000-0003-2435-4471
M Ruby SiddiquiIntegrated Outbreak Analytics, UNICEF, London, UK.
Simone E CarterPUBLIC HEALTH EMERGENCIES, UNICEF, Kinshasa, Congo (the Democratic Republic of the).ORCID http://orcid.org/0000-0003-3818-3538

Funding

World Health Organization 001
6 · The paper itself

Abstract

introductionUnderstanding sex and gender differences during outbreaks is critical to delivering an effective response. Although recommendations and minimum requirements exist, the incorporation of sex-disaggregated data and gender analysis into outbreak analytics and response for informed decision-making remains infrequent. A scoping review was conducted to provide an overview of the extent of sex-disaggregated data and gender analysis in outbreak response within low- and middle-income countries (LMICs).

methodsFive databases were searched for peer-reviewed literature examining sex- and gender-specific outcomes for communicable disease outbreaks published in English between 1 January 2012 and 12 April 2022. An adapted version of the WHO's Gender Analysis Matrix was used to synthesise evidence, which was then mapped across four phases of the outbreak timeline: prevention, detection, treatment/management and recovery.

results71 articles met inclusion criteria and were included in this review. Sex-, gender-, and pregnancy-related disparities were identified throughout all four phases of the outbreak timeline. These disparities encompassed a wide range of risk factors for disease, vulnerability, access to and use of services, health-seeking behaviour, healthcare options, as well as experiences in healthcare settings and health and social outcomes and consequences.

conclusionSignificant gender-evidence gaps remain in outbreak response. Evidence that is available illustrates that sex and gender disparities in outbreaks vary by disease, setting and population, and these differences play significant roles in shaping outbreak dynamics. As such, failing to collect, analyse or use sex-disaggregated data and gendered data during outbreaks results in less effective responses, differential adverse health outcomes, increased vulnerability among certain groups and insufficient evidence for effective prevention and response efforts. Systematic sex- and gender-based analyses to ensure gender-responsive outbreak prevention, detection, treatment/management and recovery are urgently needed.

Indexed as

COVID-19Disease OutbreaksFemaleHumansMaleSARS-CoV-2Sex FactorsGlobal HealthInfections, diseases, disorders, injuriesMaternal healthPublic HealthSystematic review

Identifiers

PMID39828430
PMCPMC11749539

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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.