Background: Many zoonotic infectious diseases have emerged and re-emerged over the last two decades. There has been a significant increase in vector-borne diseases due to climate variations that lead to environmental changes favoring the development and adaptation of vectors. This study was carried out to improve knowledge of the ecology of mosquito vectors involved in the transmission of Rift Valley fever virus (RVFV) in Senegal. Methods: An entomological survey was conducted in three Senegalese agro-systems, Senegal River Delta (SRD), Senegal River Valley (SRV) and Ferlo, during the rainy season (July to November) of 2014 and 2015. Mosquitoes were trapped using CDC light traps set at ten sites for two consecutive nights during each month of the rainy season, for a total of 200 night-traps. Ecological indices were calculated to characterize the different populations of RVFV mosquito vectors. Generalized linear models with mixed effects were used to assess the influence of climatic conditions on the abundance of RVFV mosquito vectors. Results: A total of 355,408 mosquitoes belonging to 7 genera and 35 species were captured in 200 night-traps. RVFV vectors represented 89.02% of the total, broken down as follows: Ae. vexans arabiensis (31.29%), Cx. poicilipes (0.6%), Cx. tritaeniorhynchus (33.09%) and Ma. uniformis (24.04%). Comparison of meteorological indices (rainfall, temperature, relative humidity), abundances and species diversity indicated that there were no significant differences between SRD and SRV (P = 0.36) while Ferlo showed significant differences with both (P < 0.001). Mosquito collection increased significantly with temperature for Ae. vexans arabiensis (P < 0.001), Cx. tritaeniorhynchus (P = 0.04) and Ma. uniformis (P = 0. 01), while Cx. poicilipes decreased (P = 0.003). Relative humidity was positively and significantly associated with the abundances of Ae. vexans arabiensis (P < 0.001), Cx. poicilipes (P = 0.01) and Cx. tritaeniorhynchus (P = 0.007). Rainfall had a positive and significant effect on the abundances of Ae. vexans arabiensis (P = 0.005). The type of biotope (temporary ponds, river or lake) around the trap points had a significant effect on the mosquito abundances (P < 0.001). Conclusions: In terms of species diversity, the SRD and SRV ecosystems are similar to each other and different from that of Ferlo. Meteorological indices and the type of biotope (river, lake or temporary pond) have significant effects on the abundance of RVFV mosquito vectors.

Mosquitoes are vectors of major pathogen agents worldwide. Population dynamics models are useful tools to understand and predict mosquito abundances in space and time. To be used as forecasting tools over large areas, such models could benefit from integrating remote sensing data that describe the meteorological and environmental conditions driving mosquito population dynamics. The main objective of this study is to assess a process-based modeling framework for mosquito population dynamics using satellite-derived meteorological estimates as input variables. A generic weather-driven model of mosquito population dynamics was applied to Rift Valley fever vector species in northern Senegal, with rainfall, temperature, and humidity as inputs. The model outputs using meteorological data from ground weather station vs satellite-based estimates are compared, using longitudinal mosquito trapping data for validation at local scale in three different ecosystems. Model predictions were consistent with field entomological data on adult abundance, with a better fit between predicted and observed abundances for the Sahelian Ferlo ecosystem, and for the models using in-situ weather data as input. Based on satellite-derived rainfall and temperature data, dynamic maps of three potential Rift Valley fever vector species were then produced at regional scale on a weekly basis. When direct weather measurements are sparse, these resulting maps should be used to support policy-makers in optimizing surveillance and control interventions of Rift Valley fever in Senegal.

Our understanding of the viral communities associated to animals has not yet reached the level attained on the bacteriome. This situation is due to, among others, technical challenges in adapting metagenomics using high-throughput sequencing to the study of RNA viromes in animals. Although important developments have been achieved in most steps of viral metagenomics, there is yet a key step that has received little attention: the library preparation. This situation differs from bacteriome studies in which developments in library preparation have largely contributed to the democratisation of metagenomics. Here, we present a library preparation optimized for metagenomics of RNA viruses from insect vectors of viral diseases. The library design allows a simple PCR-based preparation, such as those routinely used in bacterial metabarcoding, that is adapted to shotgun sequencing as required in viral metagenomics. We first optimized our library preparation using mock viral communities and then validated a full metagenomic approach incorporating our preparation in two pilot studies with field-caught insect vectors; one including a comparison with a published metagenomic protocol. Our approach provided a fold increase in virus-like sequences compared to other studies, and nearly-full genomes from new virus species. Moreover, our results suggested conserved trends in virome composition within a population of a mosquito species. Finally, the sensitivity of our approach was compared to a commercial diagnostic PCR for the detection of an arbovirus in field-caught insect vectors. Our approach could facilitate studies on viral communities from animals and the democratization of metagenomics in community ecology of viruses.

Rift Valley fever (RVF) is endemic in northern Senegal, a Sahelian area characterized by a temporary pond network that drive both RVF mosquito population dynamics and nomadic herd movements. To investigate the mechanisms that explain RVF recurrent circulation, we modelled a realistic epidemiological system at the pond level integrating vector population dynamics, resident and nomadic ruminant herd population dynamics, and nomadic herd movements recorded in Younoufere area. To calibrate the model, serological surveys were performed in 2015-2016 on both resident and nomadic domestic herds in the same area. Mosquito population dynamics were obtained from a published model trained in the same region. Model comparison techniques were used to compare five different scenarios of virus introduction by nomadic herds associated or not with vertical transmission in Aedes vexans. Our serological results confirmed a long lasting RVF endemicity in resident herds (IgG seroprevalence rate of 15.3%, n = 222), and provided the first estimation of RVF IgG seroprevalence in nomadic herds in West Africa (12.4%, n = 660). Multivariate analysis of serological data suggested an amplification of the transmission cycle during the rainy season with a peak of circulation at the end of that season. The best scenario of virus introduction combined yearly introductions of RVFV from 2008 to 2015 (the study period) by nomadic herds, with a proportion of viraemic individuals predicted to be larger in animals arriving during the 2 nd half of the rainy season (3.4%). This result is coherent with the IgM prevalence rate (4%) found in nomadic herds sampled during the 2 nd half of the rainy season. Although the existence of a vertical transmission mechanism in Aedes cannot be ruled out, our model demonstrates that nomadic movements are sufficient to account for this endemic circulation in northern Senegal.