Artificial Intelligence for Public Health Surveillance in Africa: Applications and Opportunities

• URL: http://arxiv.org/abs/2408.02575v1
• Date: Mon, 5 Aug 2024 15:48:51 GMT
• Title: Artificial Intelligence for Public Health Surveillance in Africa: Applications and Opportunities
• Authors: Jean Marie Tshimula, Mitterrand Kalengayi, Dieumerci Makenga, Dorcas Lilonge, Marius Asumani, Déborah Madiya, Élie Nkuba Kalonji, Hugues Kanda, René Manassé Galekwa, Josias Kumbu, Hardy Mikese, Grace Tshimula, Jean Tshibangu Muabila, Christian N. Mayemba, D'Jeff K. Nkashama, Kalonji Kalala, Steve Ataky, Tighana Wenge Basele, Mbuyi Mukendi Didier, Selain K. Kasereka, Maximilien V. Dialufuma, Godwill Ilunga Wa Kumwita, Lionel Muyuku, Jean-Paul Kimpesa, Dominique Muteba, Aaron Aruna Abedi, Lambert Mukendi Ntobo, Gloria M. Bundutidi, Désiré Kulimba Mashinda, Emmanuel Kabengele Mpinga, Nathanaël M. Kasoro,
• Abstract summary: This paper investigates the applications of AI in public health surveillance across the continent. Our paper highlights AI's potential to enhance disease monitoring and health outcomes. Key barriers to the widespread adoption of AI in African public health systems have been identified.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial Intelligence (AI) is revolutionizing various fields, including public health surveillance. In Africa, where health systems frequently encounter challenges such as limited resources, inadequate infrastructure, failed health information systems and a shortage of skilled health professionals, AI offers a transformative opportunity. This paper investigates the applications of AI in public health surveillance across the continent, presenting successful case studies and examining the benefits, opportunities, and challenges of implementing AI technologies in African healthcare settings. Our paper highlights AI's potential to enhance disease monitoring and health outcomes, and support effective public health interventions. The findings presented in the paper demonstrate that AI can significantly improve the accuracy and timeliness of disease detection and prediction, optimize resource allocation, and facilitate targeted public health strategies. Additionally, our paper identified key barriers to the widespread adoption of AI in African public health systems and proposed actionable recommendations to overcome these challenges.

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