Combining Hydrology and Mosquito Population Models to Identify the Drivers of Rift Valley Fever Emergence in Semi-Arid Regions of West Africa

Abstract

BackgroundRift 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 FindingsA 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/SignificanceOur 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.

A dynamic, climate-driven model of Rift Valley fever

“…These studies comprise theoretical exercises concentrating purely on transmission during different epidemiological states independent of climate. The effects of the environment on mosquito dynamics have been included in some other recent RVF modelling that investigate the fluctuating effects of regional seasonality using a simple oscillating temperature function (Fischer et al, 2013), spatial effects via weighted contact networks (Xue et al, 2012), hydrology (Soti et al, 2012) and effects of vaccination interventions (Chamchod et al, 2014). However, quantitative risk assessment of the impact of climate change on RVF dynamics in Africa has not been carried out.…”

Simulation Modelling of Population Dynamics of Mosquito Vectors for Rift Valley Fever Virus in a Disease Epidemic Setting

“…This study shows that daily temperature and rainfall are key ecological factors to include in models that predict episodes related to RVFV outbreak [20]. Simulations provide an ideal approach for understanding the important parameters in virus transmission dynamics with important insights to be gained in prevention and control of such epidemics.…”

Dynamic risk model for Rift Valley fever outbreaks in Kenya based on climate and disease outbreak data

“…RVF is a vector-borne disease caused by a virus that belongs to the family Bunyaviridae, genus Phlebovirus that affects domestic livestock such as sheep, cattle, camels and goats, in which animal species it causes abortions (Cook and Zumla, 2003) associated with high neonatal mortality (Davies and Martin, 2003). The RVF virus infects also humans (Soti et al, 2012). It is transmitted transovarially by Aedes or Culex mosquitoes (Hightower et al, 2012).…”

“…Major outbreaks were experienced in Egypt in 1977-1978and 1993, in the Senegal River Valley in 1987, in Madagascar in 1990, 1992, in northern Kenya and Somalia in 1997, 1998and 2007, in Saudi Arabia and Yemen in 2000, in Sudan in 2007and in Southern Africa in 2010(Soti et al, 2012, often with devastating consequences. For example, the outbreaks in Somali and Ethiopia led to a loss of USD 132 million following Saudi Arabia's imposition of a trade ban on live animals from Ethiopia, Somalia and Kenya (Rich and 2010).…”