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Integrated mapping of establishment risk for emerging vector-borne infections: a case study of canine leishmaniasis in southwest France

Authors :
Hartemink, N.A.
Vanwambeke, S.O.
Heesterbeek, J.A.P.
Rogers, D.J.
Morley, D.
Pesson, B.
Davies, C.
Mahamdallie, S.
Ready, P.
Strategic Infection Biology
Dep Gezondheidszorg Landbouwhuisdieren
UCL - SST/ELI/ELIC - Earth & Climate
Faculty of Veterinary Medicine, Utrecht University - Department of Farm Animal Health, Utrecht, The Netherlands
Spatial Ecology and Epidemiology Research Group - Department of Zoology, Oxford, United Kingdom
Source :
PLoS ONE, PLoS One, 6(8). Public Library of Science, PLoS One, Vol. 6, no. 8, p. e20817 (2011), PLoS ONE, Vol 6, Iss 8, p e20817 (2011)
Publication Year :
2011
Publisher :
Public Library of Science, 2011.

Abstract

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 R(0) map for leishmaniasis was constructed within a Geographical Information System. R(0) 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 R(0) model. The resulting maps should be considered as proofs-of-principle rather than as ready-to-use risk maps, since validation is currently not possible. 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.

Details

Language :
English
ISSN :
19326203
Database :
OpenAIRE
Journal :
PLoS ONE, PLoS One, 6(8). Public Library of Science, PLoS One, Vol. 6, no. 8, p. e20817 (2011), PLoS ONE, Vol 6, Iss 8, p e20817 (2011)
Accession number :
edsair.doi.dedup.....ca5c2fa9d12a6b1dca75db7d2e30fc79