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A generic climate-driven model to predict mosquito population dynamics : [Part A - Oral presentations]

Ezanno P., Balenghien T., Cailly P., L'Ambert G., Toty C., Tran A.. 2014. In : Proceedings ICAHS - 2nd International Conference on Animal Health Surveillance " Surveillance against the odds", The Havana, Cuba, 7-9 May 2014. s.l. : s.n., p. 50-52. International Conference on Animal Health Surveillance. 2, 2014-05-07/2014-05-09, La Havane (Cuba).

Mosquitoes are vectors of major pathogens worldwide. A good understanding and prediction of their population dynamics are needed to identify areas where there is a high risk of disease spread and persistence if pathogens were to be introduced. This issue becomes central in a context of extension of the repartition areas of certain mosquito species and with the emergence of associated vector-borne diseases. Simulation tools are pertinent to support decision makers in the surveillance of vector populations and associated vector-borne diseases. Models of vector population dynamics provide predictions of the most high risk periods in vector abundance. Therefore, they inform on the periods to be targeted by the surveillance system, which can be particularly needed in areas with a highly variable environment (seasonal environment, artificial flooding, etc.). We present here a generic climate-driven model of mosquito population dynamics which has been applied to species of the genus Anopheles, Culex and Aedes in a temperate wetland in southern France. The model predictions correctly represent the observed dynamics. A sensitivity analysis of the model enabled us to identify the most influential parameters, which should be the most precisely known for the model to end with precise predictions. This model is a flexible and efficient tool providing additional knowledge on mosquito abundance depending on local environmental factors. It should be extended then to account for the spatial heterogeneity and structure of the environment. Our model is useful to and already used by (at least) one surveillance manager of mosquito abundance (EID-Méditerrannée) in France. (Résumé d'auteur)

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