Carvalho, Bruno M., Maia, Carla, Courtenay, Orin, Llabrés-Brustenga, Alba, Lotto Batista, Martín, Moirano, Giovenale, van Daalen, Kim R., Semenza, Jan C. and Lowe, Rachel

Leishmaniases are neglected diseases transmitted by sand flies. The aim of this modelling study was to develop an indicator that tracks climatic suitability for Leishmania infantum transmission in Europe at the subnational level. Historical records of sand fly vectors, human leishmaniasis, bioclimatic indicators, and environmental variables were integrated in a machine learning framework (XGBoost) to predict suitability in two past periods (2001–2010 and 2011–2020. This study demonstrates how key epidemiological data can be combined with open-source climatic and environmental information to develop an indicator that effectively tracks spatiotemporal changes in climatic suitability and disease risk. The positive association between the model predictions and human disease incidence demonstrates that this indicator could help target leishmaniasis surveillance to transmission hotspots.

The Lancet Regional Health - Europe. June 2024