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...

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

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