. 2025 Jul 10;32(1):e101294.

doi: 10.1136/bmjhci-2024-101294.

Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol

Kerry Glover^#¹, Tabitha Osler^#^{1

2}, Kayode Adetunji^{1

3}, Tanya Akumu⁴, Gershim Asiki^{5

6}, Diana Awuor⁷, Palwendé Boua^{1

8}, Victoria Bronstein⁹, Joan Byamugisha¹⁰, Jacques D Du Toit^{11

12

13}, Barry Dwolatzky³, Jaya George^{14

15}, Paul A Harris¹⁶, Kobus Herbst^{17

18}, Karen Hofman¹⁹, Celeste Holden¹⁹, Samuel Iddi^{20

21}, Damazo T Kadengye²², Kathleen Kahn¹¹, Michelle Kamp^{1

23}, Nhlamulo Khoza^{1

2}, Faith Kimongo¹¹, Isaac Kisiangani^{5

24}, Dekuwin E Kogda⁸, Michael Klipin^{25

26}, Stephen P Levitt³, Dylan Maghini^{1

27}, Karabo Maila¹, Eric Maimela^{28

29}, Daniel Maina Nderitu^{5

30}, Ndivhuwo Makondo^{10

31}, Molulaqhooa Linda Maoyi¹⁷, Reineilwe Given Mashaba²⁸, Nkosinathi Gabriel Masilela¹¹, Theophilous Mathema¹, Phelelani Thokozani Mpangase¹, Daphine T Nyachowe^{1

32}, Daniel Ohene-Kwofie^{3

11}, Helen Robertson³¹, Skyler Speakman⁴, Evelyn Thsehla¹⁹, Siphiwe A Thwala¹⁰, Roy Zent³³, Francesc Xavier Gómez-Olivé¹¹, Chodziwadziwa W Kabudula¹¹, Patrick Opiyo Owili⁷, Catherine Kyobutungi²², Michèle Ramsay¹, Stephen Tollman^{11

34}, Scott Hazelhurst^{35

3}

Affiliations

¹ Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.
² Division of Human Genetics, University of the Witwatersrand, Johannesburg, South Africa.
³ School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.
⁴ IBM Research - Africa, Nairobi, Kenya.
⁵ Chronic Disease Management Unit, African Population and Health Research Center, Nairobi, Kenya.
⁶ Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden.
⁷ Research and Related Capacity Strengthening Unit, African Population and Health Research Center, Nairobi, Kenya.
⁸ Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Nanoro, Burkina Faso.
⁹ School of Law, University of the Witwatersrand, Johannesburg, South Africa.
¹⁰ IBM Research - Africa, Johannesburg, South Africa.
¹¹ MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand Johannesburg, Johannesburg, South Africa.
¹² Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
¹³ University of Basel, Basel, Switzerland.
¹⁴ Wits Diagnostic Innovation Hub, University of the Witwatersrand, Johannesburg, South Africa.
¹⁵ Department of Chemical Pathology, National Health Laboratory Service, Johannesburg, South Africa.
¹⁶ Departments of Biomedical Informatics, Biostatistics, Biomedical Informatics & Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
¹⁷ DSI-SAMRC South African Population Research Infrastructure Network (SAPRIN), South African Medical Research Council, Durban, South Africa.
¹⁸ Africa Health Research Institute, Durban, South Africa.
¹⁹ SAMRC/Wits Centre for Health Economics and Decision Science - PRICELESS SA, University of the Witwatersrand, Johannesburg, South Africa.
²⁰ Data Synergy and Evaluation Unit, African Population and Health Research Center, Nairobi, Kenya.
²¹ Department of Statistics and Actuarial Science, University of Ghana, Accra, Ghana.
²² African Population and Health Research Center, Nairobi, Kenya.
²³ Statistical Genetics Unit, King's College, London, UK.
²⁴ Department of Global Health, Amsterdam University Medical Centre, Amsterdam, The Netherlands.
²⁵ Department of Surgery, University of the Witwatersrand, Johannesburg, South Africa.
²⁶ WitsBits, Health Sciences Biomedical Informatics, University of the Witwatersrand, Johannesburg, South Africa.
²⁷ Department of Medicine (Hematology), Stanford University, Stanford, California, USA.
²⁸ DIMAMO Population Health Research Centre, University of Limpopo, Polokwane, South Africa.
²⁹ Department of Public Health, University of Limpopo, Polokwane, South Africa.
³⁰ School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
³¹ School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa.
³² Steve Biko Centre for Bioethics, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa.
³³ Division of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
³⁴ INDEPTH Network, Accra, Ghana.
³⁵ Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa Scott.Hazelhurst@wits.ac.za.

^# Contributed equally.

PMID: 40639840
PMCID: PMC12258287
DOI: 10.1136/bmjhci-2024-101294

Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol

Kerry Glover et al. BMJ Health Care Inform. 2025.

. 2025 Jul 10;32(1):e101294.

doi: 10.1136/bmjhci-2024-101294.

Authors

Affiliations

¹ Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.
² Division of Human Genetics, University of the Witwatersrand, Johannesburg, South Africa.
³ School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.
⁴ IBM Research - Africa, Nairobi, Kenya.
⁵ Chronic Disease Management Unit, African Population and Health Research Center, Nairobi, Kenya.
⁶ Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden.
⁷ Research and Related Capacity Strengthening Unit, African Population and Health Research Center, Nairobi, Kenya.
⁸ Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Nanoro, Burkina Faso.
⁹ School of Law, University of the Witwatersrand, Johannesburg, South Africa.
¹⁰ IBM Research - Africa, Johannesburg, South Africa.
¹¹ MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand Johannesburg, Johannesburg, South Africa.
¹² Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
¹³ University of Basel, Basel, Switzerland.
¹⁴ Wits Diagnostic Innovation Hub, University of the Witwatersrand, Johannesburg, South Africa.
¹⁵ Department of Chemical Pathology, National Health Laboratory Service, Johannesburg, South Africa.
¹⁶ Departments of Biomedical Informatics, Biostatistics, Biomedical Informatics & Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
¹⁷ DSI-SAMRC South African Population Research Infrastructure Network (SAPRIN), South African Medical Research Council, Durban, South Africa.
¹⁸ Africa Health Research Institute, Durban, South Africa.
¹⁹ SAMRC/Wits Centre for Health Economics and Decision Science - PRICELESS SA, University of the Witwatersrand, Johannesburg, South Africa.
²⁰ Data Synergy and Evaluation Unit, African Population and Health Research Center, Nairobi, Kenya.
²¹ Department of Statistics and Actuarial Science, University of Ghana, Accra, Ghana.
²² African Population and Health Research Center, Nairobi, Kenya.
²³ Statistical Genetics Unit, King's College, London, UK.
²⁴ Department of Global Health, Amsterdam University Medical Centre, Amsterdam, The Netherlands.
²⁵ Department of Surgery, University of the Witwatersrand, Johannesburg, South Africa.
²⁶ WitsBits, Health Sciences Biomedical Informatics, University of the Witwatersrand, Johannesburg, South Africa.
²⁷ Department of Medicine (Hematology), Stanford University, Stanford, California, USA.
²⁸ DIMAMO Population Health Research Centre, University of Limpopo, Polokwane, South Africa.
²⁹ Department of Public Health, University of Limpopo, Polokwane, South Africa.
³⁰ School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
³¹ School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa.
³² Steve Biko Centre for Bioethics, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa.
³³ Division of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
³⁴ INDEPTH Network, Accra, Ghana.
³⁵ Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa Scott.Hazelhurst@wits.ac.za.

^# Contributed equally.

PMID: 40639840
PMCID: PMC12258287
DOI: 10.1136/bmjhci-2024-101294

Abstract

Introduction: Multimorbidity (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.

Methods and analysis: 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 and dissemination: 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.

Keywords: data science; data visualization; machine learning; medical record linkage; public health informatics.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

**Figure 1. Action diagram of the *Multimorbidity in Africa: Digital Innovation, Visualisation and Application* process.**

**Figure 2. Project structure of the *Multimorbidity in Africa: Digital Innovation, Visualisation and Application* (MADIVA) consortium.**

See this image and copyright information in PMC

References

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1. Brady E, Castelli M, Walker R, et al. The prevalence and social determinants of multimorbidity in South Africa. World Med Health Policy. 2023;15:435–54. doi: 10.1002/wmh3.557. - DOI
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Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol

Affiliations

Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources