modeliser_pour_comprendre_et_predire_la_dynamique_des_populations_de_vecteurs_et_des_maladies_vectorielles_animales
Vector population dynamics and animal vector diseases

Model to understand and predict the dynamics of vector populations and animal vector-borne diseases and evaluate strategies for their control.

The control of vector-borne diseases and their vectors is a major animal and public health issue. A modelling approach has made it possible to integrate scattered and heterogeneous knowledge between vector species or vector-borne diseases in order to propose epidemiological models and vector population dynamics that can be used to evaluate targeted control strategies.

Context / challenges

Many vector-borne diseases have recently emerged, particularly in the Mediterranean region, in connection with global changes: climate change, but also changes in land use and intensification of human and animal transport. The recent appearance in northern Europe of BTV serotype 8 (bluetongue virus) and its wide and rapid spread has, moreover, shown the difficulty of anticipating such emergences. However, the control of vector-borne diseases is a major challenge in terms of animal and public health and also in limiting the nuisance caused by the vectors. In this context, the availability of qualitative predictive tools to evaluate ex-ante scenarios for the spread and control of vector-borne diseases or their vectors would be a major asset for animal and human health managers.
To better understand the influence of biotic (host densities, vector densities, etc.), abiotic (weather, climate, etc.) and anthropogenic (land use, etc.) factors in the spread of vector-borne diseases and the population dynamics of their vectors, modelling is a preferred approach. It allows the integration of scattered and heterogeneous knowledge between vector-borne diseases, the testing of biological hypotheses, and the ex-ante evaluation of a wide range of control strategies. The biological system to be studied and predicted is complex, relying on interactions between vector populations showing significant seasonal variations and human-managed host populations. These interactions induce the spread of pathogens and are partly driven by human decisions, particularly in terms of land use management and vector control. They evolve with global changes and the ability to predict changes in system behaviour is critical.

Results

A generic model of multi-year population dynamics of mosquitoes (major winged vectors in animal and human health) driven by climate has been developed and applied to Anopheles species in wetlands (Cailly et al., 2011b). Model predictions under current conditions are consistent with entomological data and are sensitive to variations in mortality and development, sex ratio and number of eggs laid, thus providing potential control points for the biological system. This model allows the evaluation of control strategies targeting a specific life cycle stage and time of year. The implementation of the strategies can be time-dependent or dependent on the abundance of mosquitoes in a given stage.
An epidemiological model of the spread of a vector-borne disease in a host population has been developed, taking into account the high seasonality of vector abundance and the different possible modes of transmission of the pathogen (Charron et al., 2011). It has been applied to the spread of bluetongue in cattle populations. An equivalent of the basic reproductive number (R0) in a seasonal context has been proposed (RS), providing a criterion for assessing the epidemic risk under different control scenarios, such as vaccination.

Perspectives

Developing epidemiological or vector population dynamics models that also include a spatial component would allow more accurate predictions at different scales (local to continental). Thus, the distribution of mosquito nesting sites, which is spatially heterogeneous and sometimes controllable by humans, partly explains the spatial structuring of adult mosquito populations for several major species (Cailly et al., 2011a). This factor should therefore be integrated into a model of mosquito population dynamics.
Such models would then make it possible to evaluate control strategies targeting not only hosts or vectors in time, but also in space, constituting real tools to assist in the surveillance and control of vectors and associated vector-borne diseases. Finally, they would make it possible to evaluate global change scenarios, impacting not only climate, but also land use and the movement of animals and people.

Partners

  • CIRAD UMR CMAEE & UPR AGIRs, Montpellier
  • EID-Méditerranée, Montpellier
  • IRD, Montpellier
  • Univ. Bordeaux 2, IMB, Bordeaux

Publications

  • Cailly P.*, Balenghien T. *, Ezanno P. *, Fontenille D., Toty C., Tran A.* 2011a. Role of the wetland breeding site repartition in the spatial distribution of Anopheles and Culex vectors of human diseases in Southern France. Parasites and Vectors, 4:65, doi:10.1186/1756-3305-4-65. [*contribution égale]
  • Cailly P., Tran A., Balenghien T., L’Ambert G., Toty C., Ezanno P. 2011b. A climate-driven abundance model to assess mosquito control strategies. Ecological Modelling (accepté).
  • Charron M., Langlais M., Seegers H., Ezanno P. 2011. Seasonal spread and control of Bluetongue in cattle. Journal of Theoretical Biology, 291, 1-9, doi:10.1016/j.jtbi.2011.08.041.

Partners