Valérie Soti, Annelise Tran, Yaya Thiongane, Didier Fontenille, Jean-François Guégan, Véronique Chevalier, Danny Lo Seen, Pascal Degenne, Mawlouth Diallo, Systèmes de Cultures Annuelles (UPR SCA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Animal et gestion intégrée des risques (UPR AGIRs), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut Sénégalais de Recherches Agricoles [Dakar] (ISRA), Institut Pasteur de Dakar, Réseau International des Instituts Pasteur (RIIP), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), This study was funded by EU Grant GOCE-2003-010284 EDEN (Emerging Diseases in a changing European eNvironment) and Nevantropic SAS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., We are grateful to Bernard Mondet (IRD), who shared his data (Action Concertée Incitative ‘Quantitative ecology’ -French Ministry of Research and CORUS -French Ministry of Foreign Affairs). Thanks to Thomas Balenghien (Cirad), Gregory L'Ambert (EID-Méditerranée, Montpellier, France), Florence Fouque (Pasteur Institute) and Thierry Baldet (Cirad) who shared their expertise on the mosquito parameters. We also gratefully acknowledge Agnès Bégué (Cirad), Stéphane de la Rocque (Cirad/FAO), Diam A Sow (ISRA-Dakar/Senegal), Ibra Touré (Cirad-PPZS), Eric Etter (Cirad) and Renaud Lancelot (Cirad) for their collaboration, and François Marquès from Nevantropic SAS for his support. Thanks to Raphaël Duboz (Cirad) for his advices on population modelling and sensitivity analysis. We also wish to thank the four anonymous reviewers for their comments and suggestions on the earlier version of the manuscript., European Project, Systèmes de Cultures Annuelles (UPR 102 SCA), Animal et gestion intégrée des risques (Cirad-Bios-UPR 22 AGIRs), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), and Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Background Rift Valley fever (RVF) is a vector-borne viral zoonosis of increasing global importance. RVF virus (RVFV) is transmitted either through exposure to infected animals or through bites from different species of infected mosquitoes, mainly of Aedes and Culex genera. These mosquitoes are very sensitive to environmental conditions, which may determine their presence, biology, and abundance. In East Africa, RVF outbreaks are known to be closely associated with heavy rainfall events, unlike in the semi-arid regions of West Africa where the drivers of RVF emergence remain poorly understood. The assumed importance of temporary ponds and rainfall temporal distribution therefore needs to be investigated. Methodology/Principal Findings A hydrological model is combined with a mosquito population model to predict the abundance of the two main mosquito species (Aedes vexans and Culex poicilipes) involved in RVFV transmission in Senegal. The study area is an agropastoral zone located in the Ferlo Valley, characterized by a dense network of temporary water ponds which constitute mosquito breeding sites. The hydrological model uses daily rainfall as input to simulate variations of pond surface areas. The mosquito population model is mechanistic, considers both aquatic and adult stages and is driven by pond dynamics. Once validated using hydrological and entomological field data, the model was used to simulate the abundance dynamics of the two mosquito species over a 43-year period (1961–2003). We analysed the predicted dynamics of mosquito populations with regards to the years of main outbreaks. The results showed that the main RVF outbreaks occurred during years with simultaneous high abundances of both species. Conclusion/Significance Our study provides for the first time a mechanistic insight on RVFV transmission in West Africa. It highlights the complementary roles of Aedes vexans and Culex poicilipes mosquitoes in virus transmission, and recommends the identification of rainfall patterns favourable for RVFV amplification., Author Summary Rift Valley fever (RVF) is a zoonotic disease that affects domestic livestock and humans. During inter-epizootic periods, the main infection mechanism is suspected to be through bites by infected mosquitoes, mainly of Aedes and Culex genera. In East Africa, RVF outbreaks are known to be closely associated with heavy rainfall events, unlike in the semi-arid regions of West Africa where the drivers of RVF emergence remain poorly understood. This study brings mechanistic insight to explain why reported RVF outbreaks in Northern Senegal cannot be correlated directly to rainfall. This is done through the use of a rainfall-driven model of RVF vector populations that combines a hydrological model to simulate daily water variations of mosquito breeding sites, with mosquito population models capable of reproducing the major trends in population dynamics of the two main vectors of RVF virus in Senegal, Ae. vexans and Cx. poicilipes. Results show that RVF occurs during years when both species are present simultaneously in high densities. Simulations of inter-annual variations in mosquito populations successfully explained the dates of RVF outbreaks observed between 1961 and 2003.