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Yellow fever is a vector-borne disease endemic in tropical regions of Africa, where 90% of the global burden occurs, and Latin America. It is notoriously under-reported with uncertainty arising from a complex transmission cycle including a sylvatic reservoir and non-specific symptom set. Resulting estimates of burden, particularly in Africa, are highly uncertain. We examine two established models of yellow fever transmission within a Bayesian model averaging framework in order to assess the relative evidence for each model’s assumptions and to highlight possible data gaps. Our models assume contrasting scenarios of the yellow fever transmission cycle in Africa. The first takes the force of infection in each province to be static across the observation period; this is synonymous with a constant infection pressure from the sylvatic reservoir. The second model assumes the majority of transmission results from the urban cycle; in this case, the force of infection is dynamic and defined through a fixed value of R0 in each province. Both models are coupled to a generalised linear model of yellow fever occurrence which uses environmental covariates to allow us to estimate transmission intensity in areas where data is sparse. We compare these contrasting descriptions of transmission through a Bayesian framework and trans-dimensional Markov chain Monte Carlo sampling in order to assess each model’s evidence given the range of uncertainty in parameter values. The resulting estimates allow us to produce Bayesian model averaged predictions of yellow fever burden across the African endemic region. We find strong support for the static force of infection model which suggests a higher proportion of yellow fever transmission occurs as a result of infection from an external source such as the sylvatic reservoir. However, the model comparison highlights key data gaps in serological surveys across the African endemic region. As such, conclusions concerning the most prevalent transmission routes for yellow fever will be limited by the sparsity of data which is particularly evident in the areas with highest predicted transmission intensity. Our model and estimation approach provides a robust framework for model comparison and predicting yellow fever burden in Africa. However, key data gaps increase uncertainty surrounding estimates of model parameters and evidence. As more mathematical models are developed to address new research questions, it is increasingly important to compare them with established modelling approaches to highlight uncertainty in structures and data., Author summary Yellow fever (YF) is notoriously under reported due to non-specific symptom spectrum and the true burden is highly uncertain as a result of a complex transmission cycle. As such, estimates surrounding YF burden are highly uncertain and the mechanisms behind transmission are often unclear. We assess these mechanisms and the resulting uncertainty by estimating two existing models of YF transmission within a product space framework. This allows us to produce updated estimates of transmission intensity and to compare the relative support for each model given the data. We find strong support for a model assuming a static force of infection, approximating the constant infection pressure from the sylvatic reservoir of YF. We also highlight areas where data is sparse, often the same areas estimated to have especially high transmission intensity. This is the first robust multi-model approach to applied YF modelling and provides a framework that could be extended to other disease models.

Background Rift Valley fever (RVF) is a vector-borne disease affecting ruminants and humans. Madagascar was heavily affected by RVF in 2008–2009, with evidence of a large and heterogeneous spread of the disease. The identification of at-risk environments is essential to optimize the available resources by targeting RVF surveillance in Madagascar. Herein, the objectives of our study were: (i) to identify the environmental factors and areas favorable to RVF transmission to both cattle and human and (ii) to identify human behaviors favoring human infections in Malagasy contexts. Methodology/Principal Findings First, we characterized the environments of Malagasy communes using a Multiple Factor Analysis (MFA). Then, we analyzed cattle and human serological data collected at national level using Generalized Linear Mixed Models, with the individual serological status (cattle or human) as the response, and MFA factors, as well as other potential risk factors (cattle density, human behavior) as explanatory variables. Cattle and human seroprevalence rates were positively associated to humid environments (p, Author Summary Rift Valley fever virus (RVFV) is a pathogen that causes a vector-borne tropical disease. The disease affects ruminants and humans and severely impacts the health and economy of affected countries. Madagascar was heavily affected by Rift Valley fever (RVF) in 2008–2009, with evidence of a large and heterogeneous spread of the disease. Our study aims at identifying environmental and human-related risk factors for RVFV transmission. First, we characterized Malagasy environments according to their putative influence on RVFV mosquito density and population dynamics. Then we statistically analyzed cattle and human serological data collected at a national level with the individual serological status as response, and Malagasy environments previously characterized by climatic and landscape variables as well as other potential risk factors as explanatory variables. Our results identified humid environments of the western, north-western and eastern parts of the island as risky areas. The identification of at-risk environments is essential to focus veterinary surveillance and control of RVFV.

Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health. Although several strains of these viruses had been isolated in Iran in the late 1970's, there was no recent data about the present situation at the outset of this study. Entomological investigations performed in 2009 and 2011 in Iran collected 4,770 sandflies from 10 different regions. Based on morphological identification, they were sorted into 315 pools according to species, sex, trapping station and date of capture. A phlebovirus, provisionally named Dashli virus (DASHV), was isolated from one pool of Sergentomyia spp, and subsequently DASHV RNA was detected in a second pool of Phlebotomus papatasi. Genetic and phylogenetic analyses based on complete coding genomic sequences indicated that (i) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV], (ii) there is a common ancestor to DASHV, Sandfly fever Sicilian- (SFS) and SFS-like viruses isolated in Italy, India, Turkey, and Cyprus (lineage I), (iii) DASHV is more distantly related with Corfou and Toros viruses (lineage II) although common ancestry is supported with 100% bootstrap, (iii) lineage I can be subdivided into sublineage Ia including all SFSV, SFCV and SFTV except those isolated in Iran which forms sublineage Ib (DASHV). Accordingly, we suggest to approve Sandfly fever Sicilian virus species consisting of the all aforementioned viruses. Owing that most of these viruses have been identified in human patients with febrile illness, DASHV should be considered as a potential human pathogen in Iran., Author summary Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health. Although several strains of these viruses had been isolated in Iran in the late 1970's, there was no recent data about the present situation at the outset of this study. Entomological investigations performed in 2009 and 2011 in Iran collected 4,770 sandflies from 10 different regions. A phlebovirus, provisionally named Dashli virus (DASHV), was isolated / detected in two pools. DASHV strain was isolated in cell culture and complete genome sequence was determined. Sequence analysis indicated that (i) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV], a virus that is known to cause self-resolutive incapacitating febrile illness in humans, (ii) there is a common ancestor to DASHV and all other variants of SFSV isolated in Italy, India, Turkey, and Cyprus (lineage I), (iii) DASHV is more distantly related with Corfou and Toros viruses (lineage II) although common ancestry is supported with 100% bootstrap, (iii) lineage I can be subdivided into sublineage Ia including all SFSV strains, whereas Iranian viruses are most closely related and should be individualized as DASHV (sublineage Ib). Although discovered first in the 1940's, SFSV is still listed as "tentative species" by the International Committee for Taxonomy of Viruses. Based on the results described in this study, we propose to approve Sandfly fever Sicilian virus species. Owing that most of these viruses have been identified in human patients with febrile illness, DASHV should be considered as a potential human pathogen in Iran.