Towards an Early Detection and Improved Management of Schistosomiasis in Africa Through AI and the One Health Approach

Abstract

Schistosomiasis, or bilharzia, remains one of the most widely neglected tropical diseases, representing a major public health problem, particularly in sub-Saharan Africa. Despite control efforts, gaps remain in our understanding of transmission mechanisms and the effectiveness of prevention strategies, particularly due to the complexity of interactions between human, animal and environmental factors. The One Health approach, which is still underutilized, and recent technological advances such as artificial intelligence offer promising opportunities to improve the detection and management of this disease. Using the PRISMA framework, we systematically reviewed the literature published between 2011 and 2025, focusing on AI-based methodologies and the One Health approach. However, challenges remain, including the lack of diversity in datasets, regional adaptability, and integration into existing health systems. This study highlights the transformative potential of AI combined with the One Health approach to strengthen schistosomiasis control strategies.

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