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

Gouvidé Jean Gbaguidi et al · BMC · 2026

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Abstract Background Malaria 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. Methods An 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). Results The 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. Conclusion These 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.

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APA 7

al, G. J. G. E. (2026). Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach. https://doi.org/10.1186/s12936-026-05881-5

MLA

al, Gouvidé Jean Gbaguidi et. "Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach." 2026. https://doi.org/10.1186/s12936-026-05881-5.

Chicago

al, Gouvidé Jean Gbaguidi et. 2026. "Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach.". https://doi.org/10.1186/s12936-026-05881-5.

Harvard

al, G. J. G. E. 2026, Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach, BMC, available at: https://doi.org/10.1186/s12936-026-05881-5 [Accessed 28 Jun. 2026].

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Título
Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach
Autor / colaboradores
Gouvidé Jean Gbaguidi et al
Editorial
BMC
Año de publicación
2026
ISSN
1475-2875
ISSN
1475-2875
Idioma
eng

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