Strengthening local capacity for mathematical modelling in low- and middle-income countries : the process and lessons learnt in implementing the first cohort of Nigeria malaria modelling fellowships

dc.contributor.authorKaduru, Chijioke
dc.contributor.authorIbe, Uche
dc.contributor.authorAladeshawe, Shina
dc.contributor.authorEche-George, Adaeze
dc.contributor.authorEshikhena, Ganiyat
dc.contributor.authorAadum, Dumale
dc.contributor.authorOkon, Bassey
dc.contributor.authorIorkase, Emmanuel D.
dc.contributor.authorLeghemo, Kesiye
dc.contributor.authorOgunbode, Oladipo
dc.contributor.authorOkoronkwo, Chukwu
dc.contributor.authorOkoro, Onyebuchi
dc.contributor.authorIgumbor, Ehimario Uche
dc.contributor.authorOyeyemi, Abisoye
dc.contributor.authorUhomoibhi, Perpetua
dc.contributor.authorBabatunde, Seye
dc.date.accessioned2025-09-05T08:54:19Z
dc.date.available2025-09-05T08:54:19Z
dc.date.issued2025-04
dc.descriptionDATA AVAILABILITY : Data is provided within the manuscript.
dc.description.abstractBACKGROUND : Mathematical modelling plays a crucial role in understanding malaria epidemiology and evaluating anti-malarial interventions. In sub-Saharan Africa, National Malaria Control Programs are increasingly collaborating with modellers to optimize impact within constrained fiscal environments and evaluate the effectiveness of ongoing malaria control efforts. Despite Nigeria’s National Malaria Elimination Program soliciting modelling expertise, there remains a significant capacity gap in low- and middle-income countries (LMICs), including Nigeria. To address this, the Nigerian Malaria Modelling Fellowship (MMF) adopts a one-health approach within the Nigerian Field Epidemiology and Laboratory Training Program. METHODS : The MMF aims to enhance mathematical modelling capacity among Nigerian public health professionals by increasing the number of doctoral and postdoctoral graduates proficient in using modelling for planning, program evaluation, and outcome assessment. This paper highlights the initiative’s innovative aspects and shares initial implementation insights. RESULTS : Implemented using a human-centred design, MMF is a collaborative effort involving multiple public health stakeholders. The curriculum spans four courses—Malaria, Mathematical Modelling, Evidence Translation, and Project Management—each with targeted modules. The first cohort recruitment attracted 2173 applications, rigorously screened through a five-step process, selecting 33 Fellows from all geopolitical zones of Nigeria. The cohort applies a one-health lens and includes 48% female representation. Key findings highlight the importance of government leadership, gender mainstreaming, stakeholder co-creation, leveraging existing investments, adopting best practices, and expanding engagement to meet national needs. CONCLUSION : MMF demonstrates a collaborative effort to build modelling capacity among epidemiologists and healthcare professionals in LMICs, particularly for malaria. The rigorous recruitment process underscores a strong interest in mathematical modelling. The human-centred approach has fostered government leadership, multi-stakeholder engagement, and national ownership. This paper recommends increased commitments to local capacity strengthening in LMICs and advocates for evaluating the project, including assessing Fellows’ competencies post-training to ensure effective capacity development.
dc.description.departmentSchool of Health Systems and Public Health (SHSPH)
dc.description.librarianhj2025
dc.description.sdgSDG-03: Good health and well-being
dc.description.sponsorshipThe Nigeria Malaria Modelling Fellowship is implemented with funding from the Bill and Melinda Gates Foundation.
dc.description.urihttps://malariajournal.biomedcentral.com/
dc.identifier.citationKaduru, C., Ibe, U., Aladeshawe, S. et al. Strengthening local capacity for mathematical modelling in low- and middle-income countries: the process and lessons learnt in implementing the first cohort of Nigeria malaria modelling fellowships. Malaria Journal 24, 116: 1-13 (2025). https://doi.org/10.1186/s12936-025-05345-2.
dc.identifier.issn1475-2875 (online)
dc.identifier.other10.1186/s12936-025-05345-2.
dc.identifier.urihttp://hdl.handle.net/2263/104229
dc.language.isoen
dc.publisherBioMed Central
dc.rights© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.
dc.subjectMathematical modelling
dc.subjectMalaria epidemiology
dc.subjectSub-Saharan Africa (SSA)
dc.subjectLow- and middle-income countries (LMICs)
dc.subjectMalaria modelling
dc.subjectOne Health
dc.subjectCapacity strengthening
dc.subjectCapacity building
dc.subjectNigeria
dc.titleStrengthening local capacity for mathematical modelling in low- and middle-income countries : the process and lessons learnt in implementing the first cohort of Nigeria malaria modelling fellowships
dc.typeArticle

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