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Context :

Rift Valley fever is a zoonotic vector-borne disease that occurs in Africa, the Arabian Peninsula and the southwestern islands of the Indian Ocean. It is mainly transmitted by mosquitoes of the genera Aedes and Culex, and causes waves of abortion in animal husbandry (cattle, small ruminants, dromedaries). Contact with infected animals can infect humans and in some cases lead to fatal haemorrhagic fever. In the West African Sahel, several epidemics have occurred since the end of the 1980s, and northern Senegal represents an interesting case study as it comprises two distinct ecosystems: the Senegal River valley and delta, where hosts and vectors (mainly Culex) are present all year round; and the Ferlo region, where the rainy season triggers the emergence of vectors through the creation of temporary pools, which are also staging points for transhumant animals. It is important to better understand the relative importance of the different mechanisms that can promote the start of an epidemic when the virus is introduced. A modelling approach is useful for mapping this risk on time and space scales that can only be achieved through the mobilisation of satellite data.

Results :

A new multi-host epidemiological model was developed, including cattle, small ruminants, Aedes vexans arabiensis, Culex poicilipes and Culex tritaeniorhyncus. The epidemic potential was quantified, through the number of R0 breeding, for three consecutive rainy seasons (July-November) from 2014 to 2016. Independent, weekly introduction dates were tested, in pixels of 3.5km2 (total modelled area 15,500km2).

The presence of the vectors is linked to the filling dynamics of the temporary pools, driven by a hydrological model using rainfall data. The life cycle and transmission parameters are influenced by temperature.

It is in September that the introduction of the virus can cause the most secondary cases and allow the start of an epidemic. The date of maximum risk introduction is reached earlier each year. The locations most at risk of an outbreak vary from year to year. In these high-risk locations, increasing cattle immunity would be more effective in reducing virus transmission than increasing small ruminant immunity. On the other hand, mosquito densities are such that reducing their population is not a viable risk reduction option. Sensitivity analysis of the model shows the robustness of these results, while identifying the trophic preferences of mosquitoes and the frequency of their meals as a function of temperature as key parameters requiring accurate estimation.

Perspectives :

This work should be continued to take into account the spatio-temporal transmission of the virus from possible first cases, particularly by including seasonal animal mobility. Testing climatic scenarios linked to global changes would also make it possible to anticipate the risk at Europe's doorstep.

Valorisation :

This work is part of the FORESEE project funded by the GISA metaprogramme, coordinated by Maxime Ratinier and Renaud Lancelot. It is being carried out as part of a PhD funded by the Pays-de-La-Loire region, INRAE and CIRAD..

Bibliographic references :

Cecilia H, Métras R, Fall AG, Lo MM, Lancelot R, Ezanno P. It's risky to wander in September: modelling the epidemic potential of Rift Valley fever in a Sahelian setting. 2020. Epidemics (In Press)

Mapping the epidemic potential of Rift Valley fever in northern Senegal requires the combination of complementary input data: rainfall, temperature, vector population dynamics (Aedes vexans arabiensis, Culex poicilipes and Culex tritaeniorhyncus), and animal density (cattle, small ruminants).