Evidence map›Paper›PMID 42575549›Full record

ArticleBMJ open2026

Global inequities in representation of low-income and middle-income countries in vaccine clinical trials: protocol for a systematic review and meta-epidemiological analysis.

Mansur Ramalan, Idris Yusuf, Mary Mathew, Ishaku Bako, Mustapha Umar Imam, Babamaiyaki Musa

Abstract read
In one paragraph

Article in BMJ open, 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

6 authors.

Mansur RamalanFederal University Lafia, Lafia, Nasarawa State, Nigeria mansur.ramalan@medicine.fulafia.edu.ng.ORCID http://orcid.org/0000-0002-5358-6514
Idris YusufFederal University Lafia, Lafia, Nasarawa State, Nigeria.
Mary MathewFederal University Lafia, Lafia, Nasarawa State, Nigeria.
Ishaku BakoFederal University Lafia, Lafia, Nasarawa State, Nigeria.
Mustapha Umar ImamFederal University Lafia, Lafia, Nasarawa State, Nigeria.
Babamaiyaki MusaBayero University, Kano, Kano State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionVaccines are among the most cost-effective public health interventions and remain central to global strategies for preventing and controlling infectious diseases. Evidence generated from clinical trials informs policy decisions regarding vaccine development, regulatory approval and large-scale implementation. The low-income and middle-income countries (LMICs) bear a disproportionately higher burden of vaccine-preventable diseases and are frequently the primary targets of global immunisation programmes. In spite of this, there have been long-standing concerns regarding inequities in the geographical distribution of vaccine clinical trials. Such inequities may limit the external validity and generalisability of trial findings for LMIC settings.This systematic review and meta-epidemiological analysis aims to assess the representation of LMICs in global vaccine clinical trials and to examine patterns associated with trial characteristics, sponsorship, funding source and time. METHODS AND ANALYSIS: This systematic review protocol was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) 2015 statement. Eligible studies will be identified through comprehensive searches of bibliographic databases, including MEDLINE (via PubMed), Embase, Web of Science Core Collection, Scopus and the Cochrane Central Register of Controlled Trials, as well as clinical trial registries, including the WHO International Clinical Trials Registry Platform, ClinicalTrials.gov, the EU Clinical Trials Register, the Pan African Clinical Trials Registry and ISRCTN. Published and unpublished phase I-IV interventional vaccine clinical trials conducted on human participants will be eligible without restrictions on disease area, vaccine platform, language or publication status.Title, abstract and full-text screening will be conducted independently by two reviewers. Trial-level data on geographical location, trial phase, vaccine type, study design, sponsor type, funding source, participant distribution and publication status will be extracted using a standardised form. The primary unit of analysis will be the individual clinical trial. Descriptive and meta-epidemiological analyses will be undertaken to assess patterns of LMIC representation. Multivariable logistic regression analyses will be conducted, where appropriate, to identify trial-level factors associated with LMIC participation.The primary outcome will be the proportion of vaccine clinical trials including at least one LMIC study site. Secondary outcomes will include geographical distribution by income group and region, representation by trial phase, vaccine category and platform, sponsor and funding source, temporal trends in LMIC participation, and reporting transparency assessed through concordance between trial registry records and published reports. ETHICS AND DISSEMINATION: Ethical approval is not required because this review will use publicly available data and will not involve human participants. Findings will be disseminated through peer-reviewed publications and presentations at scientific and policy forums. PROSPERO REGISTRATION NUMBER: CRD420261295568.

Indexed as

Clinical Trials as TopicDeveloping CountriesVaccinesGlobal HealthHumansMeta-Analysis as TopicResearch DesignSystematic Reviews as TopicVaccinesClinical trialsImmunotherapyMeta-AnalysisSystematic ReviewVaccination

Identifiers

PMID42575549
PMCPMC13475257

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.