Baichoo , ShakuntalaOladeji, OlubusolaVillareal, LeanneDiakabana, HuguetteOkekunle, Akinkunmi PaulMarivate, VukosiKaggwa, FredNsoesie, Elaine O.2026-04-222026-04-222025-12-20Baichoo, S., Oladeji, O., Villareal, L. et al. 2025, 'Scoping review of artificial intelligence via mobile technology and social media for health in Africa', Nature Communications, vol. 16, no. 1, art. 11288, pp. 1-11. https://doi.org/10.1038/s41467-025-64766-4.2041-1723 (online)10.1038/s41467-025-64766-4http://hdl.handle.net/2263/109678DATA AVAILABILITY STATEMENT : This study is based entirely on previously published literature; no new datasets were generated. All data used are cited in the main text and Supplementary Information.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.en© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License.Mobile technologiesSocial mediaArtificial intelligence (AI)AfricaPreferred reporting items for systematic review and meta-analysis (PRISMA)Article