BACKGROUND : In Northern Botswana, rural communities, livestock, wildlife and large numbers of mosquitoes
cohabitate around permanent waters of the Okavango Delta. As in other regions of sub-Saharan Africa, Rift Valley
Fever (RVF) virus is known to circulate in that area among wild and domestic animals. However, the diversity and
composition of potential RVF mosquito vectors in that area are unknown as well as the climatic and ecological
drivers susceptible to affect their population dynamics.
METHODS : Using net traps baited with carbon dioxide, monthly mosquito catches were implemented over four sites
surrounding cattle corrals at the northwestern border of the Okavango Delta between 2011 and 2012. The
collected mosquito species were identified and analysed for the presence of RVF virus by molecular methods. In
addition, a mechanistic model was developed to assess the qualitative influence of meteorological and
environmental factors such as temperature, rainfall and flooding levels, on the population dynamics of the most
abundant species detected (Culex pipiens).
RESULTS : More than 25,000 mosquitoes from 32 different species were captured with an overabundance of Cx.
pipiens (69,39 %), followed by Mansonia uniformis (20,67 %) and a very low detection of Aedes spp. (0.51 %). No RVF
virus was detected in our mosquito pooled samples. The model fitted well the Cx. pipiens catching results (ρ = 0.94,
P = 0.017). The spatial distribution of its abundance was well represented when using local rainfall and flooding
measures (ρ = 1, P = 0.083). The global population dynamics were mainly influenced by temperature, but both
rainfall and flooding presented a significant influence. The best and worst suitable periods for mosquito abundance
were around March to May and June to October, respectively.
CONCLUSIONS : Our study provides the first available data on the presence of potential RVF vectors that could
contribute to the maintenance and dissemination of RVF virus in the Okavango Delta. Our model allowed us to
understand the dynamics of Cx. pipiens, the most abundant vector identified in this area. Potential predictions of
peaks in abundance of this vector could allow the identification of the most suitable periods for disease occurrence
and provide recommendations for vectorial and disease surveillance and control strategies.
Additional file 2: Mapping flooding extent method. Figure in Additional
file 2. Maps of Modified Normalized Difference Water Index (MNDWI)
derived from MODIS imagery at different dates corresponding to the
Additional file 3 Detail of the ordinary differential equation system.