Rift Valley fever (RVF) is a zoonotic disease caused by a virus mainly transmitted by Aedes and Culex mosquitoes. Infection leads to high abortion rates and considerable mortality in domestic livestock. The combination of viral circulation in Egypt and Libya and the existence of unregulated live animal trade routes through endemic areas raise concerns that the virus may spread to other Mediterranean countries, where there are mosquitoes potentially competent for RVF virus (RVFV) transmission. The competence of vectors for a given pathogen can be assessed through laboratory experiments, but results may vary greatly with the study design. This research aims to quantify the competence of five major potential RVFV vectors in the Mediterranean Basin, namely Aedes detritus, Ae. caspius, Ae. vexans, Culex pipiens and Cx. theileri, through a systematic literature review and meta-analysis. We first computed the infection rate, the dissemination rate among infected mosquitoes, the overall dissemination rate, the transmission rate among mosquitoes with a disseminated infection and the overall transmission rate for these five mosquito species. We next assessed the influence of laboratory study designs on the variability of these five parameters. According to experimental results and our analysis, Aedes caspius may be the most competent vector among the five species considered.

Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility. Rift Valley fever (RVF) affects humans and livestock across Africa, South West Indian Ocean islands, and the Arabian Peninsula. This disease is one of the World Health Organization priorities and is caused by a virus which is transmitted by mosquitoes (mainly of Aedes and Culex spp. genera), but also by direct contact from livestock to humans. Mathematical models have been used in the last 20 years to disentangle RVF virus transmission dynamics. These models can further improve our understanding of processes driving outbreaks, test the efficiency of control strategies, or even anticipate possible emergence. Provided with detailed datasets, models can tailor their conclusions to specific geographical contexts and aid in decision-making in the field. This review provides a general overview of mathematical models developed to study RVF virus transmission dynamics. We describe their main results and methodological choices, and identify hurdles to be lifted. To offer innovative animal and public health value, we recommend that future models focus on the relative contribution of host species to transmission, and the role of animal mobility.

The eco-epidemiology of tick-borne diseases hinges on the abundance and distribution of hosts that sustain tick populations and the pathogens they carry. Research into the role of bird species in the feeding of Ixodes ricinus ticks, the primary tick species of veterinary and public health importance in Europe, remains scarce. This study endeavors to bridge these knowledge gaps by (i) assessing the density of feeding ticks (DFT) within a bird community to pinpoint species making substantial contributions, and (ii) exploring interannual variations in DFT over an extended timeline. Furthermore, we investigate whether variations in individual tick burden (TB) were more closely associated with the characteristics of bird species or interannual variations affecting the density of questing tick, using interannual TB variation as a surrogate. To fulfill these aims, we conducted a 13-year longitudinal study monitoring I. ricinus ticks feeding on a bird community in a periurban forest in France, covering breeding periods from 2007 to 2019. Within this community, we identified seven principal bird species significantly contributing to I. ricinus tick feeding: the Common Blackbird (Turdus merula), the Song Thrush (Turdus philomelos), the European Robin (Erithacus rubecula), the Dunnock (Prunella modularis), the Eurasian Blackcap (Sylvia atricapilla), the Great Tit (Parus major), and the Common Nightingale (Luscinia megarhynchos). Our results show that the bird community's contribution to tick feeding remained relatively consistent from year-to-year, though certain years displayed higher or lower DFT values related to the average over the study period. Moreover, five out the seven major species accounted for 80 % to 95 % of DFT annually. Consequently, we emphasized the need to broaden the scope of future research on bird contributions to tick population dynamics beyond merely thrushes (Turdidae species), to encompass a more diverse range of species, particularly those common birds that engage in ground foraging activities. Furthermore, variations in individual tick burden were predominantly influenced by the characteristics of bird species rather than by interannual variability in infestation rates. This finding suggests a significant role for species-specific traits in determining tick exposure and susceptibility. In conclusion, our study offers new insights into the medium-term dynamics of tick-bird ecological systems, underscoring the need for future study of tick populations and their interactions with vertebrate hosts to improve our understanding of tick-borne disease circulation.

Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To this day, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. In this work, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, which needed to provide a clear description of a mechanistic model with numerical application to RVF. We categorized models as theoretical, applied or grey, according to their will to represent a specific geographical context and their use of data to fulfill this intention. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models can use different tools to meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, along with a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to substantial progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be fulfilled, and modelers need to go the extra mile regarding transparency. Authors summary Rift Valley fever (RVF) affects humans and livestock across Africa, South West Indian Ocean islands, and in the Arabian Peninsula. This disease is one of the World Health Organization priorities, and is caused by a virus transmitted by Aedes and Culex spp. mosquitoes, but also directly from livestock to humans. Mathematical models have been used in the last 20 years to disentangle RVF virus transmission dynamics. These models can further our understanding of processes driving outbreaks, test the efficiency of control strategies, or even anticipate possible emergence. Provided with detailed datasets, models can tailor their conclusions to specific geographical contexts and aid in decision-making in the field. This review provides a general overview of mathematical models developed to study RVF virus transmission dynamics. We describe their main results and methodological choices, and identify hurdles to be lifted. To offer innovative animal and public health value, we recommend that future models focus on the relative contribution of host species to transmission, and the role of animal mobility.

La fièvre de la vallée du Rift (FVR) est une arbovirose zoonotique transmise par les moustiques, présentant une grande importance sanitaire et économique. De nos jours, le virus de la FVR (VFVR) circule dans toute l’Afrique subsaharienne et des foyers ont été observés en Libye en 2021, et sont régulièrement reportés en Mauritanie. Le risque d’introduction du virus en Europe est considéré comme faible, mais l’évolution de la situation épidémiologique en Afrique du Nord suscite de l’inquiétude quant à sa diffusion dans l’ouest du bassin méditerranéen. Dans ce contexte, l’objectif général de ce projet était d’identifier les zones et périodes les plus à risque de circulation du VFVR en cas d’introduction dans cette région. Nous avons dans un premier temps réalisé une synthèse des efforts de modélisation qui ont été menés sur la FVR. Puis, nous avons sélectionné Aedes caspius, Ae. vexans, Ae. detritus, Culex pipiens et Cx. theileri comme principales espèces vectrices et avons évalué leur compétence vectorielle pour le VFVR, en conduisant une méta-analyse des publications d’infections expérimentales. Nous avons simulé les dynamiques saisonnières de ces vecteurs dans le bassin méditerranéen, en adaptant un modèle existant, à l’aide de données météorologiques et de suivis de populations de moustiques. Enfin, nous avons étudié le risque de circulation du VFVR dans cette région, quantifié par le taux de reproduction de base R0, en nous appuyant sur les paramètres de compétence vectorielle et les dynamiques de population de vecteurs obtenus précédemment. Ces résultats pourraient servir à une surveillance de la FVR basée sur le risque dans le bassin méditerranéen.