Rift Valley fever vector diversity and impact of meteorological and environmental factors on Culex pipiens dynamics in the Okavango Delta, Botswana

Abstract

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.

Keywords: Botswana; Climatic factors; Culex pipiens; Flooding; Mosquito; Okavango Delta; Population dynamics modeling; Remote sensing; Rift Valley fever; Vector.

Fig. 1

Map of the study area in north-western region of the Okavango Delta

Fig. 2

Meteorological and environmental data in the study area, Okavango Delta, 2005–2012. a Rainfall. b Mean daily temperature. c Proportion of flooded area dynamics over time

Fig. 3

Diagram of the generic model of mosquito population dynamics based on life-cycle inspired from Cailly et al. [18], succession of stages (not italicized black text) and events (italicized blue text). Mosquito life-cycle contains a complete metamorphosis between aquatic juvenile stages drawn on the left of the dotted line and terrestrial adult stages on the right. As in Cailly et al. [18], females were divided into nulliparous (which have never laid eggs) and parous (which have laid eggs at least once). The green dotted box indicates the females which moved to seek a host or an oviposition site. Culex species enter diapause as young adults (top-right-arrow) while Aedes species enter diapause as egg (bottom-right-arrow)

Fig. 4

Proportion of flooded area dynamics over time in the four trapping sites, Okavango Delta, 2005–2012

Fig. 5

Confrontation between aggregated field data (red stars), simulations (coloured lines on the upper graphic) under the four scenarios (a) and environmental variations (b). Scenario 1: Temperature used as unique input to describe the Culex pipiens population dynamics. Scenario 2: Combination of temperature and rainfall used as inputs to describe the Culex pipiens population dynamics. Scenario 3: Combination of temperature and flooding used as inputs to describe the Culex pipiens population dynamics. Scenario 4: Combination of temperature, rainfall and flooding used as inputs to describe the Culex pipiens population dynamics

Fig. 6

Separate confrontation between abundance of mosquitoes collected on each field mosquito capture site and the abundance expected by site-scale simulation under scenario 4 with the Spearman’s rho coefficient

Fig. 7

Key parameters contributing to aggregated outputs variance in scenario 4. Adult mortality rates, development rate of emerging adult and sex ratio at the emergence, number of eggs laid per nulliparous female and beginning of the favourable period significantly affect the outputs of our model