Scoping review of artificial intelligence via mobile technology and social media for health in Africa

The combination of mobile technologies and social media with Artificial Intelligence (AI) opens new opportunities for multi-modal data generation, analysis, and inference for various health applications. To investigate how these tools are being used for health applications in Africa, we conduct a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. We screen 469 articles and synthesize 116. We include 29 studies documenting the use of a broad range of advanced and straightforward machine-learning techniques to study infectious and chronic diseases such as COVID-19 (4 studies, 13.8%), malaria (5, 17.2%), and cervical cancer (2, 6.9%). Countries with high internet and mobile phone penetration have higher representation. Based on identified gaps, we make research and policy recommendations to enhance the contribution of these tools in advancing health in Africa. These include investing in studies on chronic diseases and implementing frameworks to address geographic inequity.

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Publication Details

Journal
Nature Communications
Published
2025-12-20
DOI
https://doi.org/10.1038/s41467-025-64766-4
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Scoping review of artificial intelligence via mobile technology and social media for health in Africa

Shakuntala Baichoo, Olubusola Oladeji, Akinkunmi Paul Okekunle, Elaine Okanyene Nsoesie et al.
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Mobile Health and mHealth Applications
article

Scoping review of artificial intelligence via mobile technology and social media for health in Africa

Shakuntala Baichoo, Olubusola Oladeji, Akinkunmi Paul Okekunle, Elaine Okanyene Nsoesie, Vukosi N. Marivate, Huguette Diakabana, Leanne Villareal, Fred Kaggwa
article en

Abstract

The combination of mobile technologies and social media with Artificial Intelligence (AI) opens new opportunities for multi-modal data generation, analysis, and inference for various health applications. To investigate how these tools are being used for health applications in Africa, we conduct a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. We screen 469 articles and synthesize 116. We include 29 studies documenting the use of a broad range of advanced and straightforward machine-learning techniques to study infectious and chronic diseases such as COVID-19 (4 studies, 13.8%), malaria (5, 17.2%), and cervical cancer (2, 6.9%). Countries with high internet and mobile phone penetration have higher representation. Based on identified gaps, we make research and policy recommendations to enhance the contribution of these tools in advancing health in Africa. These include investing in studies on chronic diseases and implementing frameworks to address geographic inequity.

Nature CommunicationsVol. 16(1)
Boston University (US), Seoul National University (KR), Mbarara University of Science and Technology (UG), University of Ibadan (NG), Africa International University (KE), Banner Thunderbird Medical Center (US), Arizona State University (US), University of Technology, Mauritius (MU), University of Mauritius (MU), University of Pretoria (ZA), Amref Health Africa (TZ)
Bill and Melinda Gates Foundation, African Population and Health Research Center, National Institutes of Health, Fogarty International Center
Openalex Percentile: Top 24%
Mobile Health and mHealth Applications
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