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Rift Valley fever (RVF) is a severe mosquito-borne disease affecting domestic ruminants and humans, caused by a Phlebovirus (Bunyaviridae). RVF virus (RVFV) infection may result either from mosquito bites or contact with a viremic animal, or exposure to body fluids. Recently its distribution enlarged, threatening northern Africa, a large outbreak occurred in northern Mauritania in 2010, Middle East and Europe. Even if the probability of introduction and large-scale spread of RVFV in Europe is very low, localized RVF outbreaks may occur in areas where population of ruminants and potential vectors are present. The goal of this study was to identify European suitable areas for RVF transmission. We focused on the risk of transmission of RVFV to three main European potential hosts, i.e. cattle, sheep and goats, considering only the vectorial transmission. Very few is known about European mosquito competency. Based on a literature review, five mosquito species belonging to Culex and Aedes genera, present in Europe and likely to play a role in RVFV transmission in case of virus introduction were identified: Culex (Culex) pipiens, Culex (Culex) theileri, Aedes (Aedimorphus) vexans vexans, Aedes (Ochlerotatus) caspius and Aedes (Stegomyia) albopictus. We first modelled the geographic distribution of each of these five species, based on expert knowledge and using land cover (Corine Land cover database) and elevation as proxy of mosquito presence. Then, the risk of RVFV transmission was modelled using a Multi-Criteria Evaluation (MCE) approach, integrating available experimental data on vector competence, expert knowledge on abundance, host density data and literature knowledge on host sensitivity. A sensitivity analysis was performed to assess the robustness of the results with respect to expert choices in the selection, weights assignments and combination of the different factors. The resulting maps include i) five maps of vector distribution, one for each potential vector species; ii) a map of suitable areas for vectorial transmission of RVFV considering the presence of at least one of the five mosquito species, their potential competency and abundance; and iii) a map of the risk of vector- borne transmission to cattle, sheep and goats. As expected, the resulting RVFV risk maps highlighted a strong spatial heterogeneity throughout Europe. For validation, mosquito distribution maps were compared to mosquito collection data from Italy, showing a good agreement between modelled presence probability and observed presence or absence of each species. The same validation should be performed for other European countries, at least distinguishing the main European regions, i.e. Southern, Northern and Eastern Europe. Additionally, and as far as Africa is concerned, it is well known that sheep are more sensitive than goats that are themselves more sensitive than cattle. In the absence of contradictory evidence for Europe, we considered that the three main hosts were equally sensitive to the virus. This assumption need to be validated by laboratory experiments. Lastly, we did not take into account the direct transmission which is supposed to substantially support the transmission during outbreaks in Africa. The next step could be to improve this model including a direct transmission term when available. As conclusion, we found that MCE offered a valuable framework and flexible tool for the mapping of areas at risk for the transmission of a pathogen which is absent from a region. It helped identifying gaps in knowledge of the transmission of RVFV in Europe. In particular, further lab experiments are needed - as very little is known about the competence of mosquito European species, we used estimations available for African species to estimate the role of each species as potential vectors, but this extrapolation is uncertain. Given the absence of relevant models for Europe, the cost of active surveillance and the numerous potential entry ways for th

Background Rift Valley fever (RVF) is a vector-borne viral zoonosis of increasing global importance. RVF virus (RVFV) is transmitted either through exposure to infected animals or through bites from different species of infected mosquitoes, mainly of Aedes and Culex genera. These mosquitoes are very sensitive to environmental conditions, which may determine their presence, biology, and abundance. In East Africa, RVF outbreaks are known to be closely associated with heavy rainfall events, unlike in the semi-arid regions of West Africa where the drivers of RVF emergence remain poorly understood. The assumed importance of temporary ponds and rainfall temporal distribution therefore needs to be investigated. Methodology/Principal Findings A hydrological model is combined with a mosquito population model to predict the abundance of the two main mosquito species (Aedes vexans and Culex poicilipes) involved in RVFV transmission in Senegal. The study area is an agropastoral zone located in the Ferlo Valley, characterized by a dense network of temporary water ponds which constitute mosquito breeding sites. The hydrological model uses daily rainfall as input to simulate variations of pond surface areas. The mosquito population model is mechanistic, considers both aquatic and adult stages and is driven by pond dynamics. Once validated using hydrological and entomological field data, the model was used to simulate the abundance dynamics of the two mosquito species over a 43-year period (1961-2003). We analysed the predicted dynamics of mosquito populations with regards to the years of main outbreaks. The results showed that the main RVF outbreaks occurred during years with simultaneous high abundances of both species. Conclusion/Significance Our study provides for the first time a mechanistic insight on RVFV transmission in West Africa. It highlights the complementary roles of Aedes vexans and Culex poicilipes mosquitoes in virus transmission, and recommends the identification of rainfall patterns favourable for RVFV amplification.

Rift Valley Fever (RVF) is a vector-borne viral zoonosis, transmitted either through exposure to infected animals or through bites from infected mosquitoes, mainly from the Aedes or Culex genera. In semi-arid areas, water bodies, which are full during the rainy season, allow the development of Aedes and Culex mosquito species. In East Africa, RVF outbreaks are known to be closely associated with heavy rainfall events, which lead to an above normal abundance of the vectorial populations. In Senegal, there is strong evidence that the disease is endemic. Yet, the correlation found in East Africa between extreme rainfall events and RVF outbreaks occurrence is not valid. We propose here a modelling approach which makes use of remote sensing data to investigate i) the role of rainfall temporal distribution in RVF outbreaks and ii) the possibility to develop an early-warning system for RVF in Senegal. The study area is an agropastoral zone located in Northern Senegal, a region characterized by a dense network of temporary water ponds which provide suitable breeding sites to RVF vectors. A pond hydrological model is combined with a mosquito population model to predict the abundance of the two main mosquito species involved in RVF virus transmission in Senegal (Aedes vexans arabiensis and Culex poicilipes). The hydrological model uses daily rainfall as input to simulate variations of pond surface areas. The mosquito population model is mechanistic, considers both aquatic and adult stages and is driven by pond dynamics. High spatial resolution remote sensing data are used to derive the hydrological and environmental characteristics of the ponds necessary to run the models. Once validated using hydrological and entomological field data, the model was used to simulate the abundance dynamics of the two mosquito species over a 43 year period (1961-2003). Analyzing the predicted dynamics of mosquito populations with regards to the years of main outbreaks showed that the main RVF outbreaks occurred during years with simultaneous high abundances of both species. Daily satellite rainfall estimates (TRMM) were used as alternative to ground-measured rainfall data to develop a forecasting tool of RVF in Senegal. Our study provides a mechanistic insight on RVF virus transmission in Northern Senegal. It highlights the complementary roles of Aedes vexans and Culex poicilipes mosquitoes in virus transmission and the potential of remote sensing and mechanistic modelling to develop an early-warning system of RVF outbreaks in Senegal. (Texte intégral)

Les écosystèmes tropicaux d'Asie du Sud-Est connaissent des changements d'occupation du sol sans précédent, constituant une menace pour la forte biodiversité de cette région. Afin de suivre de tels changements, la télédétection est de plus en plus utilisée à différentes échelles spatiales. Nous étudions ici les changements d'occupation du sol sur une période de vingt ans, à l'échelle du paysage de sept sites d'études localisés au Cambodge, au Laos et en Thaïlande. Pour chaque site, des images à haute résolution spatiale des satellites SPOT ont été acquises à trois dates entre 1987 et 2008, ainsi que des Modèles Numériques de Surface (SPOT et SRTM DEMs). Une méthode orientée-objet de détection des changements a été appliquée à ces images pour évaluer pour chaque site d'étude i) la localisation et ii) le taux de changement d'occupation du sol. A partir des objets classifiés, nous avons également calculé des indices paysagers synthétiques reflétant la fragmentation et l'hétérogénéité du paysage. Cette analyse multi-temporelle a mis en évidence la difficulté de mettre en place un processus unique de classification comprenant de nombreux indices pour des paysages contrastés. Cependant, les techniques de classification orientées objet se sont avérées appropriées pour cartographier l'occupation du sol des différentes zones d'études, et ainsi d'en étudier les changements. Les résultats mettent en évidence différents motifs de changements d'occupation du sol, avec des taux annuels de déforestation compris entre 0,65 et 1,84 %, les changements les plus importants étant observés au Cambodge et au Laos. Par ailleurs, les indices de fragmentation révèlent des disparités entre les trois pays. Les méthodes, résultats et perspectives de ce travail sont discutés.

Leishmaniasis are among the most important vector-borne diseases being endemic in 80 countries where they constitute a major public health concern. The resurgence of cutaneous leishmaniasis (CL) in North Africa and the Middle East reflects the remarkable adaptability of the parasite in a changing environment including population movements, urbanization, and rural development. CL is endemic in Algeria where both forms have been described previously, the sporadic form caused by Leishmania infantum in the north and the classical form caused by L. major in central and southern parts of the country. In 2005, an outbreak of CL occurred in the province of Ghardaïa, located in the northern Sahara: 2,040 humans cases were recorded, many of them from urban areas, and a new enzyme variant has been described: L. killicki (MON-301). The latter species coexists sympatrically with L. major MON-25. Both species are transmitted respectively by Phlebotomus sergenti and P. papatasi, suggesting distinct eco-epidemiological patterns and specific distribution area. The aim of this study is to characterize the environmental determinants of CL in the city of Ghardaïa by using SPOT images, entomological and epidemiological collected data in order to establish a risk map for the two species. Our results show that CL due to L. killicki seem to be localized in the outskirts of the city, near foothills where the potential reservoir Massoutiera mzabi (Rodentia, Ctenodactylidae) is present, while CL due to L. major is more likely present within the city, more particularly in palm groves and gardens. This study will provide useful informations for local authorities on the respective risk area of both parasites in order to take prevention and mitigation measures to prevent CL outbreaks. (Texte intégral)

The objective of this study was to explore the potential of very high spatial resolution imagery to contribute to a better understanding of the Rift Valley Fever (RVF) transmission at the local scale in the Ferlo Region in the northern Senegal. We propose a landscape approach to map the favourable mosquitos? biotopes and to test for associations between landscape variables and RVF incidence rates around the village of Barkedji, Ferlo region, Senegal. A very high spatial resolution satellite image (2.4 m /pixel resolution) provided by the Quickbird sensor was used to detect and characterize the temporary ponds, which are the breeding sites for Aedes Vexans and Culex Poicilipes, the two main mosquito vectors of the RVF virus. We applied object-based image-processing techniques, which exploit both spectral and textural information, to provide a detailed pond map, a vegetation map around the ponds, and a general land use map. Then, we derived from these maps five landscape variables, based on bibliographic knowledge of the vector ecology: - a landscape closure index, - an index of water vegetation coverage, - and a pond density index, - the location of the pond, - the surface area of the pond. To test the relations between these landscape variables and RVF incidence, we used a beta-binomial regression model. The Akaike's information criterion allowed selecting the best fitted models. The 500-m landscape closure index was significantly correlated with higher serologic incidence (p

A case-control study at both village and farm levels was designed to investigate risk factors for highly pathogenic avian influenza H5N1 during the 2007 outbreaks in one province of Northern Vietnam. Data related to human and natural environments, and poultry production systems were collected for 19 case and 38 unmatched control villages and 19 pairs of matched farms. Our results confirmed the role of poultry movements and trading activities. In particular, our models found that higher number of broiler flocks in the village increased the risk (OR = 1.49, 95% CI: 1.12-1.96), as well as the village having at least one poultry trader (OR = 11.53, 95% CI: 1.34-98.86). To a lesser extent, in one of our two models, we also identified that increased density of ponds and streams, commonly used for waterfowl production, and greater number of duck flocks in the village also increased the risk. The higher percentage of households keeping poultry, as an indicator of households keeping backyard poultry in our study population, was a protective factor (OR = 0.95, 95% CI: 0.91-0.98). At the farm level, three risk factors at the 5% level of type I error were identified by univariate analysis: a greater total number of birds (P = 0.006), increase in the number of flocks having access to water (P = 0.027) and a greater number of broiler flocks in the farm (P = 0.049). Effect of vaccination implementation (date and doses) was difficult to investigate because of a poor recording system. Some protective or risk factors with limited effect may not have been identified owing to our limited sample size. Nevertheless, our results provide a better understanding of local transmission mechanisms of HPAI H5N1 in one province of the Red River Delta region in Vietnam and highlight the need to reduce at-risk trading and production practices.

Modelling spatial dynamics may be used to gather understanding on how insect populations develop in a given environment. Hypotheses and independent knowledge inferred from ground observations can be confronted for consistency, and the mechanisms requiring finer descriptions can also be identified. Different scenarios of pest management can then be simulated and the possible consequences of the measures taken assessed. However, spatial dynamics are expressions of multiple and complex ongoing processes, and their modelling at different temporal and spatial scales remains a challenging task. Various approaches have been proposed to address this, including cellular automata, agent-based systems, discrete event systems, system dynamics and geographic information systems, each displaying specific benefits in some domains of application, and weaknesses in others. In this area of research, we are exploring an approach based on the manipulation of graphs (mathematical object expressing a set of entities, some of which are linked) that are employed here in an innovative way for modelling landscape dynamics. Concepts essential for modellers had to be identified and formally defined. A modelling computer language (called Ocelet) was then developed, together with the grammar and syntax needed to manipulate these concepts, the compiler, and the environment/interface for building models and running simulations. Ocelet is thus both a modelling language and a simulation tool. To illustrate its usage, two case studies possibly pertinent for pest management are presented: 1) the dissemination of a pathogen among neighbouring agricultural plots, and 2) temporary pond and mosquito population dynamics for understanding Rift Valley Fever (RVF) occurrence. (Texte intégral)

Des études rétrospectives ont été menées sur la vague de foyers de 2007 dans le Nord Vietnam. Tout d'abord, une étude cas/témoins a été construite pour identifier les facteurs de risque de l'influenza aviaire hautement pathogène (IAHP) H5N1 dans une province du Nord Vietnam. Des données sur les facteurs de risque potentiels liés à l'environnement humain et naturel et au système de production ont été collectées pour 19 villages cas et 38 villages témoins non appariés. Le nombre de bandes de volailles de chair dans le village était significativement associé au risque de foyer de H5N1 (OR = 1,49, IC à 95% : 1,12-1,96), tout comme la présence d'au moins un commerçant de volailles dans le village (OR = 11,53, IC à 95% 1,34-98,86). Dans une moindre mesure, le nombre de bandes de canards dans le village et le pourcentage de la surface du village occupée par les mares et des petits cours d'eau augmentait également le risque. L'effet de la vaccination a été difficile à mesurer du fait d'un mauvais système d'enregistrement des services locaux. Ensuite, une étude à l'échelle régionale a été mise en oeuvre afin d'améliorer l'hétérogénéité spatiale et explorer des variables environnementales. Les résultats initiaux de cette étude sont également présentés.

Climate impacts vector-borne disease transmission through a complex interplay of influences on all the actors involved: the vector, the host and the pathogen. Climate change can lead to shifts in disease distribution, exposing naive host populations and potentially leading to sanitary crisis. Assessing the effects of climate change on diseases is necessary in order to better prepare and mitigate such impacts. The basic reproduction ratio (R0) measures the number of secondary cases arising from the introduction of one infected host in a susceptible population. It reflects the risk of transmission if the pathogen is introduced. Some of its parameters such as the vector biting rate, the vector mortality rate, the extrinsic incubation period and, the vector to host ratio exhibit a strong climatic dependence. Linking these parameters with climate observations or simulations allows mapping of past and future R0. We illustrate this approach by applying it to two diseases caused by Orbiviruses transmitted by Culicoides biting midges: bluetongue and African horse sickness. We map R0 anomalies for Europe for past (1961 to 2010) and future (2011 to 2050) periods and assess the uncertainty of the results presented. This approach also enables a better understanding of the underlying mechanisms involved in transmission risk increase or decrease. We discuss (i) the conditions necessary to apply this approach to other diseases, (ii) its strengths and limits, and (iii) propose entomological, epidemiological and climatic studies to further improve the approach. (Texte intégral)

We have developed an explicit spatial and temporal model to predict the population dynamics and dispersal of the two main mosquito vector species (Aedes vexans and Culex poicilipes) involved in Rift Valley fever virus (RVFV) transmission in Senegal (western Africa). Covering an area of 11x10 km around the village of Barkedji, and located in the Ferlo valley (Northern Senegal), the study area is characterized by a complex and dense network of water bodies and ponds that are filled by rainfall during the rainy season (from July to mid- October). These water bodies are known to be the principal mosquito breeding sites in the area. A spatial diffusion model (Raffy and Tran, 2005) is applied in combination with a vector population dynamic model (Soti et al., 2009), and which takes into account the hydrological conditions of the system (Soti et al., submitted). The vector population dynamic model has been more specifically derived from Porphyre et al. (2005). Daily mosquito abundance for each pond was fed into the spatial diffusion model to simulate the spread of vector populations around their breeding sites, taking into account the spatial distribution of night camps of the sensitive hosts (essentially small ruminants such as sheep) and the influence of the landscape variables (vegetation type and density) extracted from a Quickbird satellite image. We have validated the simulation results using apparent mosquito-abundance data collected during the 2002 and 2003 rainy seasons, using sheepbaited traps located at different distances from the ponds (Chevalier et al., 2004). This original approach will allow predicting how mosquitoes move and disperse spatially and temporally, such information being useful for orienting health protection measures towards areas of higher risk for RVF. (Texte intégral)

Risk factors of Rift Valley fever (RVF) emergence remain partially unknown [1]. RVF is endemic in the Ferlo area (northern Senegal).A serological study performed in this region in small ruminants associated with an entomological study showed that the risk of RVF transmission, was spatially heterogeneous [2, 3] and linked to the pond structure. In the same area, we identified from satellite images three main landscape indexes potentially linked with the vector dynamic. These indexes were included as explanatory variables in a logistic regression mixed model. The 500-m landscape closure index was significantly correlated with higher serologic incidence. These results highlight the potential of high resolution remote sensing to characterize the landscape structure at a relevant scale to describe RVF risk areas [4]. The re-emergence of the virus during rainy season in this very dry area may be explained by two processes: transovarial transmission within the vector, or introduction of the virus by nomadic ruminants coming from endemic areas. A quantitative risk assessment indicates that the risk of introduction of the virus by nomadic herds is very low. Thus, it is likely that RVF is endemic in this area as a result of transovarial transmission within the vector population. Globalisation of legal and illegal trade and travel may increase the risk of the large scale spread of the virus and introduction from endemic into disease-free areas. Assuming the virus has not survived in Yemen, data from field studies and literature was used to qualitatively assess the likelihood of ¿re-introduction¿ of RVF into Yemen through the legal and illegal importation of small ruminants from the Horn of Africa. After developing the different pathways and the matrix of likelihood combinations, first results were an overall probability of introduction assessed low outside the rainy season, medium in summer and most likely to occur via ovine males exported during festival periods. Finally, we modelled and estimated the basic reproduction number (R0) for RVF in the Ferlo region using serological data (2003-2004) with two methods: the first based on an ordinary differential equation model fitted to serological test data and the based catalytic models' theory. With the first method, the value of R0 (which gave a root mean square value of 1and and was therefore considered to be the most accurate estimate) was 1.5. With the second method, R0 values were 2.84 for young sheep and 1.69 for adults. A regional project (Indian Ocean-Southern Africa) will be implemented in the next years to test main persistence and emergence assumptions and propose control recommendations. (Texte intégral)

West Nile transmission was shown to be endemic in the Ferlo area, a sahelian part of Senegal. A serological study was carried out on horses in the Senegal river basin to assess the epidemiological status of this area for WN transmission and try to identify environmental risk factors of this transmission. Two satellite ETM+ images from the dry and wet seasons were used to provide a land-cover map of the study area. Using generalized linear mixed model and a component analysis strategy, the results showed that (i) WN virus is endemic in this region; (ii) the transmission differed with landscape despite a global high transmission level. This first landscape approach in an endemic area may provide a methodology to identify risk areas in non-endemic areas and target the surveillance.

Several studies showed that remote sensing data appear as an appropriate solution for accurately locating ponds over large areas, but there are few studies on the temporal aspect to monitor their dynamics. Here, we presented a method to monitor ponds hydrological dynamics (filling/emptying) in arid lands using a time series of MODIS/TERRA images. We studied two consecutive rainy seasons 2001 and 2002 for which we had corresponding measurements of daily water level data on several ponds. The study was conducted within a radius of approximately 13* 13 km around the village of Barkedji (15.22°N, 14.86°W) located in the Ferlo region in North-East Senegal. This area is characterized by a complex and dense network of ponds that are filled during the rainy season. To evaluate MODIS images ability to capture pond dynamics, we calculated the correlation between the NDVI pixel value and the water level data collected at three ponds (Mous, Furdu and Barkedji) using an empirical temporal cross-covariance method. The temporal study showed very good results with a maximum of cross-covariance (Mous: cov=0.69; Furdu: cov=0.77; Barkedji: cov=0.83) for [delta]t=-6 days for Mous and Furdu and [delta]t=-10 days for Barkedji pond, suggesting that multi-temporal MODIS-NDVI data can prove very efficient for monitoring the state and dynamics of little ponds (about 2000 m2) in and lands. (Texte intégral)

La superficie de la forêt malgache a considérablement diminué sous l'effet de la culture sur brûlis, pratique encore utilisée dans le nord-ouest du bassin de la Sofia. Dans cette zone, des pullulations récentes et sans précédent du criquet nomade Nomadacris septemfasciata (Serville, 1838) causant des ravages sur l'agriculture ont été observées de 2000 à 2003. Le criquet nomade a atteint la phase grégaire en formant des bandes larvaires et des essaims pour la première fois dans cette zone en 2002. La disparition de la forêt, entrave naturelle aux migrations du criquet, pourrait favoriser les migrations et permettrait le regroupement des populations acridiennes. Pour répondre à cette question, nous avons réalisé une étude diachronique par télédétection à partir de 2 images SPOT de 1986 et 2004 sur la région nord du bassin de la Sofia. L'évolution du couvert végétal met en évidence la déforestation et une fragmentation des forêts originelles. Comme l'attestent les données acridiennes, de nouvelles voies privilégiées de déplacement donnent accès à des sites de ponte auparavant inaccessibles et permettent aux criquets de se multiplier et se regrouper.

The Red locust Nomadacris septemfasciata (Serville, 1838) Orthoptera: Acrididae is found in southern Africa and on islands in the Indian Ocean. Although responsible for plagues in southern Africa, only a few local outbreaks have been reported in Madagascar. Yet, in 2002, locusts became gregarious in the Sofia basin, i.e., swarms and larval bands threatened the two main rice-producing basins of the country. The overall scope of this study is to explain this new gregarisation of the Red locust in Madagascar. Factors controlling the locust population dynamics were determined during a four year field monitoring program (2003 to 2007). The ecological requirements of this locust were assessed during the different periods of its life cycle. The evolution of the locust habitat was mapped using remotely sensed data (Spot satellite). Our results show a close connection between Red locust ecological requirements and environmental modification in the Sofia basin. First, the locust potential of each habitat at the eco-regional and macro-regional scale was quantified. Second, these habitats were mapped in 1986 and 2004. Satellite images revealed extensive deforestation thus providing new favourable breeding habitats for locusts. This environmental alteration also opened migration pathways between complementary ecological areas. The combination of both these factors allowed the Red locust gregarization to be possible. A Red locust forecasting system is outlined within the scope of a preventive control strategy. (Texte intégral)

A large number of diseases that affect humans and animals are influenced by environmental factors. For multi-host infectious diseases, various species might be involved in the transmission process and the circulation of the pathogenic agent might result from the occurrence of certain specific association(s) between host and vector species. The need to characterise multi-species assemblage requires the development of new methods to derive integrated environmental risk factors. We have given remote sensing an ecological application to study the potential distribution of West Nile virus (WNV) in the Rhone River delta in southern France. West Nile fever is a vector-borne disease transmitted in natural cycles between birds and mosquitoes. Satellite images were used to create an ecological map on land cover. Appropriate typology was employed for the description of both hosts and vectors distributions. A database including the probability of occurrence of bird and mosquito species in each landscape unit is linked to this ecological map. Spatial and temporal information on host and vector distribution is then integrated using geographic information systems. This integrative tool is designed to test some hypotheses on the epidemiological process of WNV and to identify environmental configurations and environmental changes likely to favour the emergence of WNV.

Cette étude a pour objet la définition d'un indicateur spatialisé de risque de diffusion du moucheron vecteur de la fièvre catarrhale du mouton (FCM), dans la région de Roquebrune-sur-Argens, département du Var (France). La FCM est une maladie virale affectant les ruminants, principalement les ovins. Son émergence dans l'ouest du bassin méditerranéen depuis 1998 peut être reliée à l'expansion de l'aire de répartition de son vecteur principal, le moucheron Culicoides imicola. L'installation réussie de populations de C. imicola dans le département du Var, confirmée en 2005, augmente considérablement le risque d'introduction du virus de la FCM dans cette région. Afin de contribuer à l'évaluation de ce risque, des outils géomatiques ont été utilisés ici pour cartographier les zones où C. imicola s'est potentiellement installé après son introduction dans la zone côtière. Considérant que la topographie et la catégorie de couvert végétal sont les principaux facteurs influant sur la dispersion des Culicoides à partir d'un point d'introduction, un indice de risque de diffusion a été développé tant à partir de paramètres extraits d'un modèle numérique d'altitude et de la classification d'une image satellitaire HRG de SPOT-5 à haute résolution spatiale, qu'à partir de données de piégeages entomologiques effectués en 2004. Les valeurs de cet indice ont ensuite été comparées avec les données de piégeages entomologiques réalisés en 2005. Les résultats montrent une bonne concordance entre les valeurs de l'indice calculé et l'abondance de C. imicola observée en 2005. Les perspectives de cette étude, qui souligne l'intérêt d'intégrer les outils géomatiques, dont la télédétection, dans les programmes de surveillance des maladies émergentes, sont discutées.

National audience; Depuis son apparition en 2000, quatre sérotypes de fièvre catarrhale ovine (FCO) ont été isolés en France : trois en Corse et un dans le Nord de la France. Huit ans après la première émergence, plusieurs leçons peuvent être dégagées. La répartition géographique des différentes souches apparues dans la zone euro-méditerranéenne permet de distinguer trois systèmes épidémiologiques indépendants. Au sein de ces systèmes, la capacité des insectes à transmettre la maladie est fonction de nombreux paramètres liés à l’hôte vertébré, à la souche virale et à l’insecte lui-même. Ces systèmes fonctionnant de façon différente, les approches de surveillance et de lutte contre la FCO doivent être adaptées.

In recent years, several vector-borne, parasitic or zoonotic diseases have emerged or re-emerged in different parts of the world, with major public health, socio-economic and political consequences. Emergence of these diseases is linked to climatic change, human-induced landscape changes and human activities that have affected disease ecology. The authors illustrate geographic information system-based approaches to understand epidemiological processes and predict disease patterns. Continent-wide approaches are used to explore vector and host distributions and identify areas where substantial changes in vector and vector-borne disease distributions have occurred. Time series of high-resolution satellite data and locally collected data reveal the spatial relationships between factors impacting disease dynamics. Using Rift Valley fever as a case study, a conceptual approach is proposed to integrate all of these data and to identify key parameters for disease modelling. Some of the challenges posed by different spatial and temporal scales of the biological processes and associated indicators are highlighted.

Par essence, l'épidémiologie des maladies vectorielles est fortement influencée par les conditions climatiques et météorologiques. Aussi, il est naturel de s'intéresser à l'impact des modifications climatiques sur ces maladies. Au travers de la description de l'émergence de la blue tongue en Europe et des connaissances actuelles disponibles à ce jour sur les causes de cette émergence, cet article aborde la complexité de l'analyse des écosystèmes dans lesquels apparaissent les maladies vectorielles. La comparaison des émergences de la blue tongue en Méditerranée depuis 1999 et en Europe du Nord en 2006 montre, d'une part, les limites des exercices de prédiction du risque puisque personne n'avait prévu l'épizootie due au sérotype 8 en 2006 dans une région aussi septentrionale et, d'autre part, que les conditions de ces émergences sont vraisemblablement différentes.

Landscape ecology is seldom used in epidemiology. The aim of this study is to assess the possible improvements that can be derived from the use of landscape approaches on several scales when exploring local differences in disease distribution, using bluetongue (BT) in Corsica as an example. The environment of BT-free and BT-infected sheep farms is described on a fine scale, using high resolution satellite images and a digital elevation model. Land-coverage is characterised by classifying the satellite image. Landscape metrics are calculated to quantify the number, diversity, length of edge and connectance of vegetation patches. The environment is described for three sizes of buffers around the farms. The models are tested with and without landscape metrics to see if such metrics improve the models. Internal and external validation of the models is performed and the relative impact of scale versus variables on the discriminatory ability of the models is explored. Results show that for all scales and irrespective of the number of parameters included, models with landscape metrics perform better than those without. The 1-km buffer model combines both the best scale of application and the best set of variables. It has a good discriminating ability and good sensitivity and specificity.

Due to human activities and changes in the environment, some ecosystems are acquiring the capacity to shelter major pathogens. Because environmental parameters such as climate, vegetation or land-use impact insect's bionomics, some vector and vector-borne disease distributions have significantly changed during the past years. Our aim was to study the conditions required for the settlement of a new vector in a new ecosystem, taking as example Culicoides imicola (Diptera: Ceratopogonidae), the main vector of bluetongue, in Corsica. The favourable environment for C. imicola was described using high resolution remote sensing and Geographical Information Systems (GIS). Factors likely to be related to vector distribution were extracted from a SPOT image (10 meters pixel) and from a digital elevation model (DEM). The normalized difference vegetation index (NDVI) was calculated and a supervised classification was carried out. Slope, altitude, and orientation of study sites were extracted from the DEM. Data on disease and vector were used to model the distribution of favourable sites for C. imicola using logistic regression. Data on outbreaks (farm descriptions and health status of about 100 sheep cases) highlighted the impact of latitude and some units of vegetation. Entomological data (collected during one-night catches in a hundred sites in June 2005) were compared to the neighbourhood of farms. Data, methods, results, applications and limits of the two approaches are discussed. (Texte intégral)

Du fait des changements climatiques et des actions de l'homme, de nombreux écosystèmes acquièrent la capacité d'héberger de nouveaux pathogènes majeurs. Ainsi, depuis quelques années, la répartition des vecteurs (particulièrement sensibles à leur écosystème) et des maladies qu'ils transmettent se modifie. L'objectif de ce projet est d'étudier les conditions d'installation d'un vecteur dans un nouvel écosystème en prenant l'exemple de Culicoides imicola, le moucheron vecteur de la fièvre catarrhale ovine en Corse. Nous proposons ici d'utiliser la télédétection et l'analyse paysagère pour caractériser les paysages favorables à C. imicola. Les paramètres environnementaux susceptibles d'influer sur la répartition du vecteur ont été obtenus à partir d'une image satellite SPOT (pixel de 10 m de résolution) et d'un modèle numérique de terrain. A partir de l'image, un indice de végétation (normalized difference vegetation index, NDVI) a été calculé et une classification supervisée de type orientée objet a été effectuée afin de produire une carte de végétation. Cette carte a permis de définir des indicateurs paysagers relatifs à l'agencement, la forme et la répartition des patchs (îlots) de végétation. Du modèle numérique de terrain ont été extraits la pente, l'altitude, l'ensoleillement et l'orientation. Parallèlement, des données épidémiologiques concernant les caractéristiques des élevages ovins et leur statut vis-à-vis de la fièvre catarrhale ovine ont été recueillies et intégrées à un système d'information géographique. Pour expliquer la survenue de foyers de fièvre catarrhale ovine, les voisinages des élevages sains et infectés ont été comparés à trois niveaux d'échelle. Les résultats font ressortir le rôle de la latitude, de certaines classes de végétation et du NDVI. Le choix des données et des méthodes mises en oeuvre, ainsi que les résultats et les perspectives en termes de surveillance sanitaire sont discutés. (Texte intégral)

Rift valley fever (RVF) is an arthropod borne disease produced by a Bunyavirus belonging to the genus Phlebovirus. Several species of Aedes and Culex are the vectors of this virus that affects sheep, goats, buffalos, cattle, camels and human beings. The human disease is well known, especially during periods of intense epizootic activity. The initial description of the disease dates back to 1930. Until 2000, this disease was only described in Africa, and then outbreaks were also declared in the Kingdom of Saudi Arabia (2000-2001 and 2004) and in Yemen (2000-2001). Animal and human cases were recorded. This work presents a retrospective summary of the data collected on animal RVF cases during this epidemic in Yemen. Results from several RVF surveys were gathered from the Yemeni vet services and FAO experts. Geographical data (topographic maps and data freely available on internet) were used for the location of outbreaks. After cleaning checking and standardisation of location names, all data were introduced into a GIS database. The spatial distribution of outbreaks was then studied at two scales: national level and local scale in the Wadi Mawr area (Tihama plain, Western coast of Yemen).

The effects of climate change on vector-borne diseases are currently widely discussed. Special attention has been focused on the unprecedented emergence of Bluetongue (BT) in Europe. In previous studies, low-resolution (1km2) satellite-derived data have been used to model the distribution of Culicoides imicola, the major vector in south-western Europe. To understand local differences in distribution of BT outbreaks in southern Corsica, the environment of BT-free and BT-infected sheep farms was described at a finer scale using high resolution remote sensing data (SPOT satellite, pixel of 10x10 m) and a digital elevation model (DEM). From the DEM, topographic variables such as mean altitude, slope, sunshine and aspect were obtained. Land-cover information was produced by classifying the satellite image with a supervised object-oriented nearest-neighbour method. Finally, landscape metrics were calculated to evaluate the number, diversity, length of edge and connectance of vegetation patches. A geographical information system was developed to extract these data in the neighbouring of sheep farms. As little is known on the flight range and bionomics of C. imicola, the environment was described at three scales: within a 500 m, 1 km or 2 km radius buffer around the sheep farms. Models highlighted the role of environmental variables such as latitude, sunshine, and some vegetation types such as prairies. The model developed at 1 km had the highest AUC receiver operating characteristic (ROC AUC = 0,90) which represents the best trade-off between specificity and sensitivity. Validation of this model was carried out on the same data set (sensitivity and specificity = 85%) as well as on a new data set originating from the region of Ajaccio (Corsica) situated 40 km north of the study area. Data, methods, results, possible applications in disease-free areas and limits of this approach are discussed. (Texte intégral)

Le travail de thèse vise à modéliser la dynamique spatiale et temporelle d'une maladie à transmission vectorielle comme la dengue, à partir de données environnementales extraites d'images de télédétection. Un modèle de diffusion, basé sur des données entomologiques et sur des para-mètres environnementaux issus d'une image satellitale, est proposé pour décrire la dynamique des moustiques vecteurs de la maladie. Un système d'équations différentielles permet ensuite de décrire les processus de transmission entre les hôtes et les vecteurs. Les modèles de la diffusion de populations d'insectes et de la dynamique de maladies vectorielles sont appliqués sur différents exemples (zones géographiques, insectes vecteurs, maladies) afin d'illustrer et valider la méthode. Un système de surveillance intégrant les outils géomatiques à différents niveaux (recueil des données, analyse, modélisation, aide à la décision) est finalement proposé. Ce travail est réalisé pour le cas de la dengue en Guyane mais avec la volonté de développer une méthode générique, transposable à d'autres contextes épidémiologiques et géographiques. L'approche développée permet d'envisager de nouvelles applications de la télédétection à l'épidémiologie.