Background

Zoonotic visceral leishmaniasis is endemic in the Mediterranean Basin, where the dog is the main reservoir host. The disease’s causative agent, Leishmania infantum, is transmitted by blood-feeding female sandflies. This paper reports an integrative study of canine leishmaniasis in a region of France spanning the southwest Massif Central and the northeast Pyrenees, where the vectors are the sandflies Phlebotomus ariasi and P. perniciosus.

Methods

Sandflies were sampled in 2005 using sticky traps placed uniformly over an area of approximately 100 by 150 km. High- and low-resolution satellite data for the area were combined to construct a model of the sandfly data, which was then used to predict sandfly abundance throughout the area on a pixel by pixel basis (resolution of c. 1 km). Using literature- and expert-derived estimates of other variables and parameters, a spatially explicit R0 map for leishmaniasis was constructed within a Geographical Information System. R0 is a measure of the risk of establishment of a disease in an area, and it also correlates with the amount of control needed to stop transmission.

Conclusions

To our knowledge, this is the first analysis that combines a vector abundance prediction model, based on remotely-sensed variables measured at different levels of spatial resolution, with a fully mechanistic process-based temperature-dependent R0 model. The resulting maps should be considered as proofs-of-principle rather than as ready-to-use risk maps, since validation is currently not possibly. The described approach, based on integrating several modeling methods, provides a useful new set of tools for the study of the risk of outbreaks of vector-borne diseases.