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

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 Appli...

Full description

Saved in:
Bibliographic Details
Main Authors: Kobus Herbst, Stephen Tollman, Kathleen Kahn, Francesc Xavier Gómez-Olivé, Jaya George, Catherine Kyobutungi, Karen Hofman, Gershim Asiki, Michèle Ramsay, Daniel Ohene-Kwofie, Chodziwadziwa W Kabudula, Helen Robertson, Isaac Kisiangani, Palwende Boua, Eric Maimela, Damazo T Kadengye, Michelle Kamp, Daniel Maina Nderitu, Phelelani Thokozani Mpangase, Kayode Adetunji, Samuel Iddi, Skyler Speakman, Scott Hazelhurst, Kerry Glover, Tabitha Osler, Tanya Akumu, Diana Awuor, Victoria Bronstein, Joan Byamugisha, Jacques D Du Toit, Barry Dwolatzky, Paul A Harris, Celeste Holden, Nhlamulo Khoza, Faith Kimongo, Dekuwin E Kogda, Michael Klipin, Stephen P Levitt, Dylan Maghini, Karabo Maila, Ndivhuwo Makondo, Molulaqhooa Linda Maoyi, Reineilwe Given Mashaba, Nkosinathi Gabriel Masilela, Theophilous Mathema, Daphine T Nyachowe, Evelyn Thsehla, Siphiwe A Thwala, Roy Zent, Patrick Opiyo Owili
Format: Article
Language:English
Published: BMJ Publishing Group 2025-07-01
Series:BMJ Health & Care Informatics
Online Access:https://informatics.bmj.com/content/32/1/e101294.full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849320173212794880
author Kobus Herbst
Stephen Tollman
Kathleen Kahn
Francesc Xavier Gómez-Olivé
Jaya George
Catherine Kyobutungi
Karen Hofman
Gershim Asiki
Michèle Ramsay
Daniel Ohene-Kwofie
Chodziwadziwa W Kabudula
Helen Robertson
Isaac Kisiangani
Palwende Boua
Eric Maimela
Damazo T Kadengye
Michelle Kamp
Daniel Maina Nderitu
Phelelani Thokozani Mpangase
Kayode Adetunji
Samuel Iddi
Skyler Speakman
Scott Hazelhurst
Kerry Glover
Tabitha Osler
Tanya Akumu
Diana Awuor
Victoria Bronstein
Joan Byamugisha
Jacques D Du Toit
Barry Dwolatzky
Paul A Harris
Celeste Holden
Nhlamulo Khoza
Faith Kimongo
Dekuwin E Kogda
Michael Klipin
Stephen P Levitt
Dylan Maghini
Karabo Maila
Ndivhuwo Makondo
Molulaqhooa Linda Maoyi
Reineilwe Given Mashaba
Nkosinathi Gabriel Masilela
Theophilous Mathema
Daphine T Nyachowe
Evelyn Thsehla
Siphiwe A Thwala
Roy Zent
Patrick Opiyo Owili
author_facet Kobus Herbst
Stephen Tollman
Kathleen Kahn
Francesc Xavier Gómez-Olivé
Jaya George
Catherine Kyobutungi
Karen Hofman
Gershim Asiki
Michèle Ramsay
Daniel Ohene-Kwofie
Chodziwadziwa W Kabudula
Helen Robertson
Isaac Kisiangani
Palwende Boua
Eric Maimela
Damazo T Kadengye
Michelle Kamp
Daniel Maina Nderitu
Phelelani Thokozani Mpangase
Kayode Adetunji
Samuel Iddi
Skyler Speakman
Scott Hazelhurst
Kerry Glover
Tabitha Osler
Tanya Akumu
Diana Awuor
Victoria Bronstein
Joan Byamugisha
Jacques D Du Toit
Barry Dwolatzky
Paul A Harris
Celeste Holden
Nhlamulo Khoza
Faith Kimongo
Dekuwin E Kogda
Michael Klipin
Stephen P Levitt
Dylan Maghini
Karabo Maila
Ndivhuwo Makondo
Molulaqhooa Linda Maoyi
Reineilwe Given Mashaba
Nkosinathi Gabriel Masilela
Theophilous Mathema
Daphine T Nyachowe
Evelyn Thsehla
Siphiwe A Thwala
Roy Zent
Patrick Opiyo Owili
author_sort Kobus Herbst
collection DOAJ
description 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.
format Article
id doaj-art-82b17f04004640b8b0dd722788a1d87a
institution Kabale University
issn 2632-1009
language English
publishDate 2025-07-01
publisher BMJ Publishing Group
record_format Article
series BMJ Health & Care Informatics
spelling doaj-art-82b17f04004640b8b0dd722788a1d87a2025-08-20T03:50:11ZengBMJ Publishing GroupBMJ Health & Care Informatics2632-10092025-07-0132110.1136/bmjhci-2024-101294Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocolKobus Herbst0Stephen Tollman1Kathleen Kahn2Francesc Xavier Gómez-Olivé3Jaya George4Catherine Kyobutungi5Karen Hofman6Gershim Asiki7Michèle Ramsay8Daniel Ohene-Kwofie9Chodziwadziwa W Kabudula10Helen Robertson11Isaac Kisiangani12Palwende Boua13Eric Maimela14Damazo T Kadengye15Michelle Kamp16Daniel Maina Nderitu17Phelelani Thokozani Mpangase18Kayode Adetunji19Samuel Iddi20Skyler Speakman21Scott Hazelhurst22Kerry Glover23Tabitha Osler24Tanya Akumu25Diana Awuor26Victoria Bronstein27Joan Byamugisha28Jacques D Du Toit29Barry Dwolatzky30Paul A Harris31Celeste Holden32Nhlamulo Khoza33Faith Kimongo34Dekuwin E Kogda35Michael Klipin36Stephen P Levitt37Dylan Maghini38Karabo Maila39Ndivhuwo Makondo40Molulaqhooa Linda Maoyi41Reineilwe Given Mashaba42Nkosinathi Gabriel Masilela43Theophilous Mathema44Daphine T Nyachowe45Evelyn Thsehla46Siphiwe A Thwala47Roy Zent48Patrick Opiyo Owili49Africa Health Research Institute, Somkhele, South Africa1 SAMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, South Africa2University of the Witwatersrand, Johannesburg, South AfricaAfrican Population and Health Research Center, Nairobi, KenyaSAMRC/Centre for Health Economics and Decision Science—PRICELESS SA, School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa1 Chronic Disease Management Unit, African Population and Health Research Center, Nairobi, KenyaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Faculty of Health Sciences, Johannesburg, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaSchool of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South AfricaEmerging and Re-emerging Infectious Diseases Unit, African Population and Health Research Center, Nairobi, KenyaClinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, Ouagadougou, Burkina FasoDIMAMO PHRC, University of Limpopo, Polokwane, South AfricaAfrican Population and Health Research Center, Nairobi, KenyaDivision of Human Genetics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaAfrican Population and Health Research Center (APHRC), APHRC Campus, Nairobi, KenyaSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaAfrican Population and Health Research Center (APHRC), APHRC Campus, Nairobi, KenyaIBM Research Africa, Nairobi, KenyaSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaIBM Research – Africa, Nairobi, KenyaResearch and Related Capacity Strengthening Unit, African Population and Health Research Center, Nairobi, KenyaSchool of Law, University of the Witwatersrand, Johannesburg, South AfricaIBM Research – Africa, Johannesburg, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand Johannesburg, Johannesburg, South AfricaSchool of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South AfricaDepartments of Biomedical Informatics, Biostatistics, Biomedical Informatics & Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USASAMRC/Wits Centre for Health Economics and Decision Science – PRICELESS SA, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand Johannesburg, Johannesburg, South AfricaClinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Sante, Nanoro, Burkina FasoDepartment of Surgery, University of the Witwatersrand, Johannesburg, South AfricaSchool of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaIBM Research – Africa, Johannesburg, South AfricaDSI-SAMRC South African Population Research Infrastructure Network (SAPRIN), South African Medical Research Council, Durban, South AfricaDIMAMO Population Health Research Centre, University of Limpopo, Polokwane, South AfricaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand Johannesburg, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaSydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South AfricaSAMRC/Wits Centre for Health Economics and Decision Science – PRICELESS SA, University of the Witwatersrand, Johannesburg, South AfricaIBM Research – Africa, Johannesburg, South AfricaDivision of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USAResearch and Related Capacity Strengthening Unit, African Population and Health Research Center, Nairobi, KenyaIntroduction 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.https://informatics.bmj.com/content/32/1/e101294.full
spellingShingle Kobus Herbst
Stephen Tollman
Kathleen Kahn
Francesc Xavier Gómez-Olivé
Jaya George
Catherine Kyobutungi
Karen Hofman
Gershim Asiki
Michèle Ramsay
Daniel Ohene-Kwofie
Chodziwadziwa W Kabudula
Helen Robertson
Isaac Kisiangani
Palwende Boua
Eric Maimela
Damazo T Kadengye
Michelle Kamp
Daniel Maina Nderitu
Phelelani Thokozani Mpangase
Kayode Adetunji
Samuel Iddi
Skyler Speakman
Scott Hazelhurst
Kerry Glover
Tabitha Osler
Tanya Akumu
Diana Awuor
Victoria Bronstein
Joan Byamugisha
Jacques D Du Toit
Barry Dwolatzky
Paul A Harris
Celeste Holden
Nhlamulo Khoza
Faith Kimongo
Dekuwin E Kogda
Michael Klipin
Stephen P Levitt
Dylan Maghini
Karabo Maila
Ndivhuwo Makondo
Molulaqhooa Linda Maoyi
Reineilwe Given Mashaba
Nkosinathi Gabriel Masilela
Theophilous Mathema
Daphine T Nyachowe
Evelyn Thsehla
Siphiwe A Thwala
Roy Zent
Patrick Opiyo Owili
Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
BMJ Health & Care Informatics
title Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
title_full Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
title_fullStr Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
title_full_unstemmed Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
title_short Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol
title_sort leveraging data science to understand and address multimorbidity in sub saharan africa the madiva protocol
url https://informatics.bmj.com/content/32/1/e101294.full
work_keys_str_mv AT kobusherbst leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT stephentollman leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT kathleenkahn leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT francescxaviergomezolive leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT jayageorge leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT catherinekyobutungi leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT karenhofman leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT gershimasiki leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT micheleramsay leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT danielohenekwofie leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT chodziwadziwawkabudula leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT helenrobertson leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT isaackisiangani leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT palwendeboua leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT ericmaimela leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT damazotkadengye leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT michellekamp leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT danielmainanderitu leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT phelelanithokozanimpangase leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT kayodeadetunji leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT samueliddi leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT skylerspeakman leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT scotthazelhurst leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT kerryglover leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT tabithaosler leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT tanyaakumu leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT dianaawuor leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT victoriabronstein leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT joanbyamugisha leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT jacquesddutoit leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT barrydwolatzky leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT paulaharris leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT celesteholden leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT nhlamulokhoza leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT faithkimongo leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT dekuwinekogda leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT michaelklipin leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT stephenplevitt leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT dylanmaghini leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT karabomaila leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT ndivhuwomakondo leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT molulaqhooalindamaoyi leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT reineilwegivenmashaba leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT nkosinathigabrielmasilela leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT theophilousmathema leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT daphinetnyachowe leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT evelynthsehla leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT siphiweathwala leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT royzent leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol
AT patrickopiyoowili leveragingdatasciencetounderstandandaddressmultimorbidityinsubsaharanafricathemadivaprotocol