Evidence map›Paper›PMID 41864970›Full record

ArticleMalaria journal2026

Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach.

Gouvidé Jean Gbaguidi, Mor Absa Loum, Lucien Diégane Gning, Aboudou Karime Tahiho, Elhadj Marouf Diallo, Ousmane Koutou, Andre Dembélé, Nikita Topanou, Guillaume K Ketoh

Abstract read
In one paragraph

Article in Malaria journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Gouvidé Jean GbaguidiWest African Science Service Centre On Climate Change and Adapted Land Use (WASCAL), Faculty of Human and Social Sciences, Department of Geography, University of Lomé, Lomé, Togo. gouvidejeang@gmail.com.
Mor Absa LoumUFR des Sciences de L'Ingénieur, Université Iba Der Thiam de Thiès, Thiès, Sénégal.
Lucien Diégane GningWest Africa Mathematical Modeling Capacity Development (WAMCAD), Université Iba Der Thiam, Thiès, Sénégal.
Aboudou Karime TahihoCentre de Recherche Pour la Lutte Contre les Maladies Infectieuses Tropicales (CReMIT), Abomey-Calavi, Benin.
Elhadj Marouf DialloCentre de Recherche et de Formation en Infectiologie de Guinée (CERFIG), Université Gamal Abdel Nasser de Conakry, Conakry, Guinée.
Ousmane KoutouCU-K/Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso.
Andre DembéléFaculté des Sciences et Techniques de Bamako (FST), Campus Universitaire de Badalabougou, Rue Léopold Sédar Senghor, BP E3206, Bamako, Mali.
Nikita TopanouKaba Laboratory of Chemical Research and Application (LaKReCA), Department of Chemistry, Faculty of Science and Technic of Natitingou, University of Abomey, Abomey, Benin.
Guillaume K KetohLaboratory of Ecology and Ecotoxicology, Department of Zoology, Faculty of Sciences, University of Lomé, 1BP: 1515, Lomé, Togo.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalaria remains a major public health challenge in Benin, particularly among children under five years of age. Despite the wide deployment of vector control measures the disease burden remains high. Based on modeling approach, this study evaluates the potential impact and effectiveness of the introduction of the RTS, S/ASO1 malaria vaccine on the reduction of malaria-related morbidity in the province of Couffo.

methodsAn Epidemiological Multi-Diseases Model (EMOD) was parameterised using entomological, epidemiological, and climatic data from Benin covering the period 2010-2023. The RTS,S/AS01 vaccine was implemented via the Expanded Programme on Immunisation (EPI) strategy used to track children under five years old in 1000 populations. Nine scenarios were simulated, combining different coverage levels and dose schedules, alongside a baseline scenario without vaccination. One-way ANOVA and Tukey's HSD post hoc test were computed to assess differences between scenarios and to identify the best-performing scenario. Data processing, visualisation, and analysis were performed in R version 4.5.1 (2025-06-13 ucrt).

resultsThe simulations revealed a substantial reduction in malaria burden associated with increasing vaccine coverage. Scenarios with higher coverage and booster doses achieved greater declines in both parasite prevalence, severe and clinical cases. Scenario 9, with 90% coverage and two boosters, resulted in the highest proportion, with 9.8% of PfPR averted, 11.06% of cases averted, and 21.83% of severe cases averted over 2030, demonstrating the synergistic effect of extended immunity through booster administration. Temporal analyses from 2024 to 2030 indicated a sustained decline in malaria incidence under the booster strategies, whereas limited gains were observed in scenarios with lower coverage.

conclusionThese findings support policy efforts to integrate RTS,S/AS01 into Benin's Expanded Programme on Immunisation (EPI) and highlight the importance of continuous surveillance to monitor vaccine performance under real-world conditions.

Indexed as

MalariaMalaria, FalciparumMalaria VaccinesBeninChild, PreschoolHumansModels, TheoreticalVaccines, SyntheticMalaria VaccinesRTS,S-AS01 vaccineVaccines, SyntheticEMOD modelMalaria controlPublic healthRTS,S/AS01 vaccine

Identifiers

PMID41864970
PMCPMC13126881

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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.