Know more

Abstract :

Mosquitoes are sources of nuisances and vectors of major pathogens for humans and animals. Despite fighting facilities, controlling their populations remains a stake constained by a precise knowledge of their dynamics in space and time. This PhD aims at identifying biotic and abiotic factors affecting the spatio-temporal population dynamics of mosquitoes. An integrative modelling approach, linked to the use of a geographical informative system (GIS), statistical analysis and observational data, enabled to represent mosquito population dynamics to better understand it and to identify efficient control strategies. A generic deterministic climate-driven model represents the mosquito life cycle over several years. This model applied to Anopheles species in a rural humid areas (Camargue, France) is consistent with the entomological data. It is sensitive to variations in mortality, development, sex ratio and number of eggs laid. It enables to evaluate control strategies targeting a stage of the life cycle and a period of the year. Having demonstrated that breeding sites distribution partially explained the spatial population structure, this factor and the host-seeking behaviour has been retained to drive adult movements. A spatial component was incorporated to the model via the representation of a real landscape and movements on this landscape. First results show that the landscape heterogeneity and its evolution over time influence the distribution and abundance in mosquitoes.

Key words :

Mechanistic model, population dynamics, spatio-temporal, mosquito, climate, landscape, GIS, simulation, sensitivity analysis, control strategies