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dc.contributor.authorGlover K.
dc.contributor.authorOsler, T.
dc.contributor.authorAdetunji, K.
dc.contributor.authorAkumu, T.
dc.contributor.authorAsiki, G.
dc.contributor.authorAwuor, D.
dc.contributor.authorBoua, P.
dc.contributor.authorBronstein, V.
dc.contributor.authorByamugisha, J.
dc.contributor.authorDu Toit, J. D.
dc.contributor.authorDwolatzky, B.
dc.contributor.authorGeorge, J.
dc.contributor.authorHarris, P. A.
dc.contributor.authorHerbst, K.
dc.contributor.authorHofman, K.
dc.contributor.authorHolden, C.
dc.contributor.authorIddi, S.
dc.contributor.authorKadengye, D. T.
dc.contributor.authorKahn, K.
dc.contributor.authorKamp, M.
dc.contributor.author� Hazelhurst, S.
dc.date.accessioned2025-12-12T05:09:16Z
dc.date.available2025-12-12T05:09:16Z
dc.date.issued2025
dc.identifier.urihttps://doi.org/10.1136/bmjhci-2024-101294
dc.identifier.urihttp://knowhub.aphrc.org/handle/123456789/2658
dc.description.abstractMultimorbidity (MM), defined as two or more chronic diseases in an individual, is linked to adverse outcomes. MM is increasing in sub-Saharan Africa due to rapidly advancing epidemiological and social transitions. The Multimorbidity in Africa: Digital Innovation, Visualisation and Application Research Hub (MADIVA) aims to address MM by developing data science solutions informed by stakeholder engagement. MADIVA uses complex, individual-level datasets from research centres in rural Bushbuckridge, South Africa and urban Nairobi, Kenya. These datasets will be harmonised, linked and curated, and then used to develop MM risk prediction models, novel data science methods and interactive dashboards for research and clinical use. Pilot projects and mentorship programmes will support data science capacity development. Ethics approval has been granted. Dissemination will occur through scientific meetings and publications. MADIVA is committed to making data FAIR: findable, accessible, interoperable and reusable.
dc.publisherBMJ Health & Care Informatics
dc.subjectMultimorbidity
dc.subjectData science
dc.subjectRisk prediction models
dc.subjectHealth systems innovation
dc.subjectSub-Saharan Africa
dc.subjectFAIR data
dc.titleLeveraging Data Science to Understand and Address Multimorbidity in Sub-Saharan Africa: The MADIVA Protocol.


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