Leishmaniasis in Morocco: Epidemiology, Transmission Dynamics, and the Potential of Artificial Intelligence for...

Leishmaniases are neglected tropical diseases caused by Leishmania parasites and transmitted by infected phlebotomine sand flies, and they remain a major public health challenge in Morocco. The burden is dominated by cutaneous leishmaniasis (CL) and visceral leishmaniasis (VL), mainly associated with Leishmania major, Leishmania tropica, and L. infantum. Despite long-standing national control efforts aligned with the Sustainable Development Goals and the national ambition to eliminate leishmaniasis as a public health problem by 2030, transmission persists and continues to expand in some areas. Climate change, urbanization, and socioeconomic inequities are reshaping vector and reservoir distributions and intensifying human exposure, whereas emerging insecticide resistance threatens the sustainability of current vector-control approaches. In parallel, recent advances in artificial intelligence (AI) offer new opportunities to strengthen surveillance, diagnosis, and targeted interventions, yet their application to leishmaniasis control in Morocco remains limited. This narrative review synthesizes recent evidence on the epidemiology, transmission cycles, vectors, reservoirs, diagnostic approaches, and control strategies of leishmaniasis in Morocco, and critically discusses how AI-enabled tools, such as predictive risk mapping, automated vector identification, and image-based clinical decision support, could help address operational gaps. By integrating AI into existing public health frameworks and reinforcing data quality and capacity building, Morocco could improve early detection, optimize resource allocation, and accelerate progress toward the 2030 elimination goal.