A Regional Atlas of Phlebotomine Sand Fly Vectors of Leishmaniasis in Eastern Africa (1845-2025): Harmonized Historical Records and an Interactive Surveillance Dashboard.

Leishmaniasis remains a major neglected tropical disease in Eastern Africa, where transmission is driven by the ecological diversity and geographic distribution of phlebotomine sand flies. Despite their epidemiological importance, regional sand fly occurrence data remain fragmented across historical reports, institutional archives, and biodiversity repositories, limiting their accessibility and reuse for ecological and epidemiological research. Here, we present the first harmonized regional atlas of phlebotomine sand flies for Eastern Africa, integrating records from Djibouti, Ethiopia, Kenya, Somalia, South Sudan, Sudan, Tanzania, and Uganda. The curated dataset comprises 1,745 geo-referenced occurrence records representing 299,583 specimens collected from 365 unique sampling locations between 1906 and 2025. In total, 67 sand fly species were documented, revealing pronounced spatial, temporal, taxonomic, and methodological heterogeneity, with Kenya, Ethiopia, and Sudan exhibiting the greatest documented diversity and surveillance intensity, while substantial sampling gaps remained in several countries. To enhance the analytical value of the atlas, we integrated geographically contextualized GenBank molecular records and developed the first interactive regional visual analytics dashboard for Eastern African sand flies, enabling dynamic exploration of species distributions, abundance patterns, sampling methods, molecular information, and surveillance coverage through interactive maps and charts. Finally, we demonstrate the practical utility of the atlas using a proof-of-concept species distribution modelling workflow for the principal visceral leishmaniasis vectors Phlebotomus orientalis and Ph. martini, illustrating how the harmonized database can support reproducible ecological modelling and disease risk mapping. Together, the regional atlas, molecular integration, interactive dashboard, and modelling framework provide a standardized digital resource for vector surveillance, biodiversity research, ecological modelling, and evidence-based leishmaniasis risk assessment across Eastern Africa.