The Intersection of Digital Health and Fascioliasis: A Narrative Review
DOI:
https://doi.org/10.23434/Abstract
Fascioliasis, a foodborne and waterborne zoonotic disease caused by the liver flukes Fasciola hepatica and F. gigantica, remains a critical neglected tropical disease (NTD) that undermines public health and agricultural economies worldwide. Traditional control measures are hindered by late-stage clinical detection, a shortage of trained microscopists in endemic rural sectors, and a lack of active, unified surveillance. This paper examines how digital health innovations—specifically artificial intelligence (AI) computer vision, mobile health (mHealth), and geographic information systems (GIS)—are modernizing the diagnosis, treatment management, and epidemiological mapping of fascioliasis. By transitioning diagnostics from manual microscopy to expert-verified edge AI and integrating climate-driven machine learning models, digital health offers a scalable framework to achieve the WHO elimination targets.
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