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Rift Valley fever (RVF) has been reported in the sub-Saharan region of Africa, Egypt and Arabian Peninsula - Yemen and Saudi Arabia, over the past 20 years and is a threat to both the animal and human populations in Tunisia. Tunisia is considered as a high-risk country for the introduction of RVF due to the informal movements of diseased animals already reported in the neighboring countries. The objective of this study was to assess the status of RVF in small ruminants and camels in Tunisia. A risk-based serological survey was conducted to evaluate the presence of RVF based on spatial qualitative risk analysis (SQRA). Samples were collected from small ruminants (sheep and goats) (n = 1,114), and camels (n = 173) samples, belonging to 18 breeders in 14 governorates between November 2017 and January 2018. Samples were tested using an RVF specific multispecies competitive ELISA. Out of the 1,287 samples tested for the presence of RVF IgG antibodies by ELISA, only one positive sample 0.07% (1/1 287) was detected but not confirmed with the virus neutralization test (VNT) used for confirmation. So far, no RVF outbreaks have been reported in Tunisia and our study confirmed the absence of RVF in livestock up to January 2018. Further investigations are needed to confirm the RVF-free status of Tunisia today., QRA methodology, Risk mapping, Survey, Tunisia, Rift valley fever, Small ruminants, Camels

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

International audience; The concept of One Health (OH) promotes the decompartmentalisation of human, animal, and ecosystem health for the more efficient and sustainable governance of complex health issues. This means that traditional boundaries between disciplines and sectors must be transgressed and that all relevant stakeholders must be involved in the definition and management of health problems. International efforts have been made to strengthen collaboration across sectors and disciplines and OH surveillance is strongly encouraged at global, national and local-level to efficiently manage hazards involving humans, animals and ecosystems.This concept is intuitively appealing and would suggest the enhanced performance and cost-effectiveness of surveillance systems, as compared to more conventional approaches. Nevertheless, confusion and uncertainty regarding the practical application, outcomes and impacts prevail. We believe that this is due to the lack of a conceptual and methodological framework which would (i) define the characteristics of OH surveillance, and (ii) identify the appropriate mechanisms for inter-sectoral and multi-disciplinary collaboration, to ensure that the surveillance system performs well, with regard to the objective, the context and the health hazard under surveillance.The objective of the study is to define the organisational and functional characteristics of OH surveillance systems, the context in which they are implemented, as well as the influential factors which may obstruct or support their implementation and performance. To achieve this, a systematic literature review of existing OH surveillance systems was conducted using the Prisma guidelines. The selected systems were assessed according to 38 predetermined variables. These allowed the characterisation of their objectives, organisation, functioning, performance and benefits. Data extraction was conducted using a spreadsheet and a database was built using an electronic multiple-choice questionnaire.The literature search identified a total of 1635 records. After the screening phase, 31 references were kept and 22 additional references retrieved from bibliographies were added. From these 53 selected documents, we retrieved 41 different surveillance systems in line with the definition proposed in this study. The analysis of this database enabled the identification of different dimensions and areas of collaboration. Barriers and levers for the implementation of OH surveillance systems were also identified and discussed.Based on our results, we propose a framework to characterise the organisation of collaboration for the governance and operation of an effective OH surveillance system.

Foot and mouth disease (FMD) is a highly contagious viral disease that affects all Artiodactyla. Seven immunologically distinct serotypes of FMD virus (FMDV) exist. In Chad, although FMD is included in the list of diseases monitored by the Chadian Animal Disease Surveillance Network (REPIMAT), the epidemiological situation remains unclear. A serological survey was conducted in the cattle population in eight of the nine administrative regions of the country (those regions with the highest cattle densities), to evaluate the prevalence and serotypes of circulating FMDV.A total of 796 sera from randomly selected cattle were analysed at the World Organisation for Animal Health/Food and Agriculture Organization of the United Nations FMD Reference Laboratory at the Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna(IZSLER), in Brescia (Italy). An enzyme-linked immunosorbent assay (ELISA), called 3ABC ELISA, was used to detect antibodies against non-structural proteins (NSPs), as well as a series of six competitive ELISAs to detect and serotype antibodies against the structural proteins of FMDV serotypes O, A, SAT 1, SAT 2, Asia 1 and C. Based on the detection of anti-NSP antibodies, the animal-level seroprevalence was 35.6%(95% confidence interval [CI]: 32.2-38.9) and the herd-level seroprevalence was 62.3% (95%CI: 53.0-71.5). FMD was present in all livestock administrative divisions surveyed, with a higher prevalence in southern regions, which are characterised by higher rainfall and humidity and more important transboundary animal movements. Cattle aged more than four years had a higher seroprevalence, which may be due to repeated exposure. Semi-sedentary farming and transhumance were also risk factors. Antibodies against serotypes A, O, SAT 1 and SAT 2 were detected.

International audience; Unravelling the ecological structure of emerging plant pathogens persisting in multi-host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs. We designed a mechanistic-statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Susceptible-Infected-Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data. We applied our approach to French surveillance data on Xylella fastidiosa, a multi-host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985. Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs.

International audience; AbstractThe first pan-European harmonized active epidemiological surveillance program on honeybee colony mortality (EPILOBEE) was set up across 17 European Member States to estimate honeybee colony mortality over winter and during the beekeeping season. In nine Member States, overwinter losses were higher and statistically different from the empirical level of 10 % under which the level of overwinter mortality was considered as acceptable with usual beekeeping conditions. In four other countries, these losses were lower. Using multivariable Poisson regression models, it was showed that the size of the operation and apiary and the clinically detected varroosis, American foulbrood (AFB), and nosemosis before winter significantly affected 2012–2013 overwinter losses. Clinically detected diseases, the size of the operation and apiary, and the non-participation to a common veterinary treatment significantly affected 2013 summer losses. EPILOBEE was a prerequisite to implement future projects studying risk factors affecting colony health such as multiple and co-exposure to pesticides.

International audience; Mycobacterium bovis infection was first described in free-ranging wildlife in France in 2001, with subsequent detection in hunter-harvested ungulates and badgers in areas where outbreaks of bovine tuberculosis (TB) were also detected in cattle. Increasing concerns regarding TB in wildlife led the French General Directorate for Food (DGAL) and the main institutions involved in animal health and wildlife management, to establish a national surveillance system for TB in free-ranging wildlife. This surveillance system is known as “Sylvatub.” The system coordinates the activities of various national and local partners. The main goal of Sylvatub is to detect and monitor M. bovis infection in wildlife through a combination of passive and active surveillance protocols adapted to the estimated risk level in each area of the country. Event-base surveillance relies on M. bovis identification (molecular detection) (i) in gross lesions detected in hunter-harvested ungulates, (ii) in ungulates that are found dead or dying, and (iii) in road-killed badgers. Additional targeted surveillance in badgers, wild boars and red deer is implemented on samples from trapped or hunted animals in at-risk areas. With the exception of one unexplained case in a wild boar, M. bovis infection in free-living wildlife has always been detected in the vicinity of cattle TB outbreaks with the same genotype of the infectious M. bovis strains. Since 2012, M. bovis was actively monitored in these infected areas and detected mainly in badgers and wild boars with apparent infection rates of 4.57–5.14% and 2.37–3.04%, respectively depending of the diagnostic test used (culture or PCR), the period and according to areas. Sporadic infection has also been detected in red deer and roe deer. This surveillance has demonstrated that M. bovis infection, in different areas of France, involves a multi-host system including cattle and wildlife. However, infection rates are lower than those observed in badgers in the United Kingdom or in wild boars in Spain.

Preparedness against vector-borne threats depends on the existence of a long-term, sustainable surveillance of vector-borne disease and their relevant vectors. This work reviewed the availability of such surveillance systems in five European countries (Denmark, France, The Netherlands, Sweden and United Kingdom, part of the CoVetLab network). A qualitative assessment was then performed focusing on surveillance directed particularly to BTV-8. Information regarding surveillance activities were reviewed for the years 2008 and 2012. The results were then complemented with a critical scoping review of the literature aimed at identifying disease surveillance strategies and methods that are currently suggested as best suited to target vector-borne diseases in order to guide future development of surveillance in the countries in question.Passive surveillance was found to be efficient for early detection of diseases during the early phase of introduction into a free country. However, its value diminished once the disease has been established in a territory. Detection of emerging diseases was found to be very context and area specific, and thus active surveillance designs need to take the available epidemiological, ecological and entomological information into account. This was demonstrated by the effectiveness of the bulk milk surveillance in detecting the first case in Sweden, highlighting the need for output based standards to allow the most effective, context dependent, surveillance strategies to be used. Preparedness was of fundamental importance in determining the timeliness of detection and control in each country and that this in turn was heavily influenced by knowledge of emerging diseases in neighboring countries. Therefore it is crucial to share information on outbreaks between researchers and decision-makers and across borders continuously in order to react timely in case of an outbreak. Furthermore, timely reaction to an outbreak was heavily influenced by availability of control measures (vaccines), which is also strengthened if knowledge is shared quickly between countries. The assessment of the bluetongue surveillance in the affected countries showed that the degree of voluntary engagement varied, and that it is important to engage the public by general awareness and dissemination of results. The degree of engagement will also aid in establishing a passive surveillance system.

Quantitative information about equine mortality is relatively scarce, yet it could be of great value for epidemiology purposes. Several European projects based on the exploitation of data from rendering plants have been developed to improve livestock surveillance. Similar data are available for equines in France but have never been studied to date. The objective of this research was to evaluate the potential of the French Ministry of Agriculture's Fallen Stock Data Interchange (FSDI) database to provide quantitative mortality information on the French equine population. The quality of FSDI equine data from 2011 to 2014 was assessed using complementary data registered in the French equine census database, SIRE. Despite a perfectible quality, the FSDI database proved to be a valuable source for studying the basal patterns of mortality over time in the French equine population as illustrated by the spatial representation of the number of deaths. However, improvements in the FSDI database are needed, in particular regarding the registration of animal identification numbers, in order to detail equine mortality for epidemiology purposes.

Unravelling the ecological structure of emerging plant pathogens persisting in multi-host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs. We designed a mechanistic-statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Suscepti-ble–Infected–Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data. We applied our approach to French surveillance data on Xylella fastidiosa, a multi-host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985. Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs.

Bovine tuberculosis (bTB) is a common disease of cattle and wildlife, with economic repercussions and implications for animal and human health. The surveillance of bTB in wildlife is particularly important, to shed light on the epidemiological role of wild species and for the adaptation of control measures. In France, a bTB surveillance system for free-ranging wildlife, the Sylvatub system, was launched in 2011 on wild boars, red deer, roe deer and badgers. It relies on active and passive surveillance activities, constrained by practical difficulties, such as the accessibility of wild animals, and regulatory rules for the trapping of badgers, for example. We report here the first assessment of stakeholders' perceptions of the Sylvatub system and its acceptability, based on 20 individual semi-structured interviews with three types of stakeholder (collectors, coordinators, officers) in areas with different rates of bTB infection. With the caveat that these findings cannot be assumed to be representative of the national situation, we found that the Sylvatub system was considered useful by all the stakeholders interviewed. Those from the world of hunting participate in surveillance mostly to help livestock farmers, who are not systematically involved in bTB surveillance in wildlife. Many practical and regulatory constraints were raised, which could be offset by recognition of the work done by the "hunting community", to maintain the willingness of these individuals to participate. We also identified a need for improvements in communication and information. Qualitative information, such as that collected here, is essential to improve our understanding of the reasons favoring and disfavoring participation in surveillance, and should be taken into account in the evaluation process. These results are relevant to hunters and to veterinary authorities wishing to identify the determinants of participation in the Sylvatub system. They could provide support for decision-making processes to improve surveillance strategies.

Background From 2006 to 2010, France experienced two bluetongue epidemics caused by serotype 1 (BTV-1) and 8 (BTV-8) which were controlled by mass vaccination campaigns. After five years without any detected cases, a sick ram was confirmed in August 2015 to be infected by a BTV-8 strain almost identical to that circulating during the previous outbreak. By then, part of the French cattle population was expected to be still protected, since bluetongue antibodies are known to last for many years after natural infection or vaccination. The objective of this study was to estimate the proportion of cattle in France still immune to BTV-8 at the time of its re-emergence in 2015. Results We used BTV group-specific cELISA results from 8525 cattle born before the vaccination ban in 2013 and 15,799 cattle born after the ban. Samples were collected from January to April 2016 to estimate seroprevalence per birth cohort. The overall seroprevalence in cattle at national and local levels was extrapolated from seroprevalence results per birth cohort and their respective proportion at each level. To indirectly assess pre-immune status of birth cohorts, we computed prevalence per birth cohort on infected farms in autumn 2015 using 1377 RT-PCR results. These revealed limited BTV circulation in 2015. Seroprevalence per birth cohort was likely to be connected to past exposure to natural infection and/or vaccination with higher seroprevalence levels in older animals. A seroprevalence of 95% was observed for animals born before 2008, of which > 90% were exposed to two compulsory vaccination campaigns in 2008-2010. None of the animals born before 2008 were found to be infected, unlike 19% of the young cattle which had never been vaccinated. This suggests that most ELISA-positive animals were pre-immune to BTV-8. We estimated that 18% (from 12% to 32% per département) of the French cattle population was probably pre-immune in 2015. Conclusions These results strongly suggest a persistence of antibodies for at least 5-6 years after natural infection or vaccination. The herd immunity of the French cattle population probably limited BTV circulation up to 2015, by which time more than 80% of cattle were naive. Electronic supplementary material The online version of this article (10.1186/s12917-018-1388-1) contains supplementary material, which is available to authorized users.

BGPI: équipe 6Paper based on work presented at the Joint EFSA-EPPO Workshop: Modelling in Plant Health – how can models support risk assessment of plant pests and decision-making? 12th–14th December 2016, Parma, Italy; International audience; The optimization of management strategies for plant diseases is a difficult task because of the complexity and variability of epidemic dynamics. Thanks to their ability to numerically simulate many scenarios, models can be used to estimate epidemiological parameters, assess the effectiveness of different management strategies and optimize them. This article presents the PESO (parameter estimation–simulation–optimization) modelling framework to help improve plant disease management strategies. This framework is based on (i) the characterization of the epidemic dynamics to estimate key epidemiological parameters, (ii) the use of spatially explicit models to simulate epidemic dynamics and disease management, and (iii) the use of numerical optimization methods to identify better management strategies. This approach is generic and can be applied to many diseases. The work presented here focuses on sharka (caused by Plum pox virus), which has a worldwide impact on the Prunus industry, and is associated with huge disease management costs in many countries, especially in France.

Bovine tuberculosis (bTB) is a common disease in cattle and wildlife, with health, zoonotic and economic implications. Infected wild animals, and particularly reservoirs, could hinder eradication of bTB from cattle populations, which could have an important impact on international cattle trade. Therefore, surveillance of bTB in wildlife is of particular importance to better understand the epidemiological role of wild species and to adapt the control measures. In France, a bTB surveillance system for free-ranging wildlife, the Sylvatub system, has been implemented since 2011. It relies on three surveillance components (SSCs) (passive surveillance on hunted animals (EC-SSC), passive surveillance on dead or dying animals (SAGIR-SSC) and active surveillance (PSURV-SSC)). The effectiveness of the Sylvatub system was previously assessed, through the estimation of its sensitivity (i.e. the probability of detecting at least one case of bTB infection by each SSC, specie and risk-level area). However, to globally assess the performance of a surveillance system, the measure of its sensitivity is not sufficient, as other factors such as economic or socio-economic factors could influence the effectiveness. We report here an estimation of the costs of the surveillance activities of the Sylvatub system, and of the cost-effectiveness of each surveillance component, by specie and risk-level, based on scenario tree modelling with the same tree structure as used for the sensitivity evaluation. The cost-effectiveness of the Sylvatub surveillance is better in higher-risk departments, due in particular to the higher probability of detecting the infection (sensitivity). Moreover, EC-SSC, which has the highest unit cost, is more efficient than the surveillance enhanced by the SAGIR-SSC, due to its better sensitivity. The calculation of the cost-effectiveness ratio shows that PSURV-SSC remains the most cost-effective surveillance component of the Sylvatub system, despite its high cost in terms of coordination, sample collection and laboratory analysis.

Integrated approach to identify terms for monitoring disease emergence on the web.Terms are extracted automatically from disease outbreak web pages.Domain experts identify the terms relevant to characterise a disease emergence.Relevant terms are used as queries to mine the web. Timeliness and precision for detection of infectious animal disease outbreaks from the information published on the web is crucial for prevention against their spread. The work in this paper is part of the methodology for monitoring the web that we currently develop for the French epidemic intelligence team in animal health. We focus on the new and exotic infectious animal diseases that occur worldwide and that are of potential threat to the animal health in France.In order to detect relevant information on the web, we present an innovative approach that retrieves documents using queries based on terms automatically extracted from a corpus of relevant documents and validated with a consensus of domain experts (Delphi method). As a decision support tool to domain experts we introduce a new measure for ranking of extracted terms in order to highlight the more relevant terms. To categorise documents retrieved from the web we use Naive Bayes (NB) and Support Vector Machine (SVM) classifiers.We evaluated our approach on documents on African swine fever (ASF) outbreaks for the period from 2011 to 2014, retrieved from the Google search engine and the PubMed database. From 2400 terms extracted from two corpora of relevant ASF documents, 135 terms were relevant to characterise ASF emergence. The domain experts identified as highly specific to characterise ASF emergence the terms which describe mortality, fever and haemorrhagic clinical signs in Suidae.The new ranking measure correctly ranked the ASF relevant terms until position 161 and fairly until position 227, with areas under ROC curves (AUCs) of 0.802 and 0.709 respectively.Both classifiers were accurate to classify a set of 545 ASF documents (NB of 0.747 and SVM of 0.725) into appropriate categories of relevant (disease outbreak) and irrelevant (economic and general) documents.Our results show that relevant documents can serve as a source of terms to detect infectious animal disease emergence on the web.Our method is generic and can be used both in animal and public health domain.

In a context of intensification of international trade and travels, the transboundary spread of emerging human or animal pathogens represents a growing concern. One of the missions of the national veterinary services is to implement international epidemiological intelligence for a timely and accurate detection of emerging animal infectious diseases (EAID) worldwide, and take early actions to prevent their introduction on the national territory. For this purpose, an efficient use of the information published on the web is essential. The authors present a comprehensive method for identification of relevant associations between terms describing clinical signs and hosts to build queries to monitor the web for early detection of EAID. Using text and web mining approaches, they present statistical measures for automatic selection of relevant associations between terms. In addition, expert elicitation is used to highlight the most relevant terms and associations among those automatically selected. The authors assessed the performance of the combination of the automatic approach and expert elicitation to monitor the web for a list of selected animal pathogens. (Resume d'auteur)

International audience; We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.

International audience; Background: Regular and relevant evaluations of surveillance systems are essential to improve their performance and cost-effectiveness. With this in mind several organizations have developed evaluation approaches to facilitate the design and implementation of these evaluations. Methods: In order to identify and to compare the advantages and limitations of these approaches, we implemented a systematic review using the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Results: After applying exclusion criteria and identifying other additional documents via citations, 15 documents were retained. These were analysed to assess the field (public or animal health) and the type of surveillance systems targeted; the development process; the objectives; the evaluation process and its outputs; and the attributes covered. Most of the approaches identified were general and provided broad recommendations for evaluation. Several common steps in the evaluation process were identified: (i) defining the surveillance system under evaluation, (ii) designing the evaluation process, (iii) implementing the evaluation, and (iv) drawing conclusions and recommendations. Conclusions: A lack of information regarding the identification and selection of methods and tools to assess the evaluation attributes was highlighted; as well as a lack of consideration of economic attributes and sociological aspects.

National audience; L’anémie infectieuse des équidés (AIE) est une maladie virale des équidés, dont la prévalence en France a fortement chuté depuis les années 1980 mais pour laquelle des cas sporadiques ou groupés sont encore régulièrement recensés. Le système de surveillance français comporte plusieurs dispositifs assurant une surveillance évènementielle ou programmée. L’objectif de ce travail était d’évaluer l’ensemble du système de surveillance de l’AIE, à l’aide de la méthode semi-quantitative OASIS (variante « flash ») afin d’identifier des axes d’amélioration. Les points forts majeurs identifiés sont la qualité du diagnostic de laboratoire, la simplicité et la rapidité des procédures de déclaration. Les principales recommandations portent sur une meilleure formalisation des objectifs de surveillance (pouvant conduire à une évolution des modalités de surveillance), un renforcement de la cohésion entre les dispositifs et une meilleure structuration de l’organisation institutionnelle centrale : unité centrale d’animation, comité de pilotage, comité scientifique et technique. Il ressort également de cette évaluation la nécessité d’améliorer la gestion et le traitement des données, en particulier leur centralisation, leur analyse épidémiologique régulière et le recours accru aux échanges informatisés pour les résultats d’analyses de laboratoire. Le travail conduit a aussi permis de montrer que l’utilisation de la méthode OASIS sous sa forme simplifiée « flash » était globalement bien acceptée par les partenaires du système de surveillance. Elle a permis en outre d’identifier avec un rapport temps/efficacité satisfaisant les principaux points faibles et de proposer des grandes améliorations du système.

The One Health concept recognizes that human health, animal health and environmental health areinterconnected and promotes multisectoral and multidisciplinary collaboration to efficiently manage health issues atthe human-animal-environment interface. One Health surveillance is strongly encouraged as it suggests theenhanced performance and cost-effectiveness of surveillance. Nevertheless, surveillance systems continue to bedeveloped and operated in a highly sectoral approach. We argue that the challenging operationalization of OneHealth surveillance is partly due to the existence of confusion and uncertainty regarding its practical application aswell as its added value comparing to sectoral surveillance components operating independently.In this context, we developed a conceptual and methodological framework to help the implementation ofOne Health surveillance. First, we characterised One Health surveillance and its application contexts using asystematic literature review of existing One Health surveillance systems followed by an expert opinion elicitation.Then, we mobilized two approaches, stakeholder analysis and companion modelling, to develop and apply twoinnovative methods to facilitate the application of the One Health concept by surveillance actors. Finally, weidentified specific attributes to support the development of a tool aiming at evaluating the quality andappropriateness of implemented collaboration to meet the collaborative objectives. Along with other projects led byresearch teams across the world, our research work contributes to the promotion of One Health surveillance.; Le concept One Health (Une seule santé) reconnaît une interconnexion entre la santé animale, la santé humaine et la santé des écosystèmes. Il encourage des efforts collaboratifs entre secteurs et disciplines pour aborder plus efficacement les problématiques sanitaires à l'interface homme-animal-environnement. En matière de surveillance sanitaire, ce concept est très largement promu car il laisse présager une amélioration de la performance épidémiologique et économique de la surveillance. Cependant, les systèmes de surveillance continuent le plus souvent à opérer en silo avec des dispositifs sectoriels très peu connectés. Nous pensons que le manque d’opérationnalisation de la surveillance One Health relève en partie de la persistance de confusions et d’incertitudes sur son application pratique et sur sa valeur ajoutée par rapport à la juxtaposition de dispositifs sectoriels fonctionnant indépendamment.Dans ce contexte, nous avons développé un cadre conceptuel et méthodologique pour favoriser la mise en oeuvre du concept One Health dans le domaine de la surveillance. Pour cela, nous avons tout d’abord caractérisé la surveillance One Health et ses contextes d’application en conduisant une revue systématique de littérature des systèmes One Health existants, suivie d’une élicitation d’opinions d’experts. Puis, nous avons mobilisé deux approches, l’analyse des acteurs et la modélisation d’accompagnement, pour développer et tester de nouvelles méthodes pour aider les acteurs de la surveillance dans la mise en oeuvre du concept One Health. Enfin, nous avons défini des attributs spécifiques pour développer un outil d’évaluation de la qualité et de la pertinence de la collaboration mise en oeuvre dans un système de surveillance pour répondre aux objectifs collaboratifs. Ces travaux participent, en synergie avec des travaux conduits par d’autres équipes de recherche, à la promotion de la surveillance One Health.

How to identify effective strategies to manage the epidemics impacting crops?The answer to this question is not obvious because of the complexity of epidemics (they simultaneously depend on biological processes, patch organization in the landscape, and human interventions). To answer that question, models can be used because of their ability to simulate many scenarios. Indeed, they can enable to estimate epidemiological parameters, to assess the efficiency of different management strategies and to optimize them.In this context, we developed a generic framework for in silico optimization of plant disease management strategies at the landscape scale. This framework is based on (i) the characterization of the epidemic dynamics to estimate its key parameters, (ii) the use of a spatially explicit model to simulate the dynamics and management of this disease and (iii) the use of numerical optimization methods to identify efficient management strategies. Here, we apply this approach to sharka, caused by Plum pox virus. This disease has a worldwide impact on the Prunus industry and is associated with huge management costs in many countries. In France, the management strategy for this disease principally consists of orchard surveillance, removal of trees that might contribute to the epidemic propagation, and plantation bans.My PhD indicates that some strategies should be more profitable than the one currently applied in France. These strategies require less orchard surveillance and do not impose any plantation ban. It turns out that some of these strategies are efficient for all tested landscape types, which may be interesting in practice for risk managers. This approach was applied to the sharka, but could be transposed to optimize the management of other epidemics.; Comment identifier des stratégies efficaces pour gérer les épidémies affectant les cultures ?La réponse à cette question n’est pas évidente du fait de la complexité des épidémies (elles dépendent à la fois de processus biologiques, de l’organisation des parcelles dans le paysage, et des interventions humaines). Pour y répondre, des modèles peuvent être utilisés en raison de leur capacité à simuler de nombreux scénarios. En effet, ils peuvent permettre d’estimer des paramètres épidémiologiques, d’évaluer l'efficacité de différentes stratégies de gestion et de les optimiser.Dans ce contexte, nous avons développé une approche générique pour optimiser in silico la gestion d’une maladie des plantes à l’échelle du paysage. Cette approche est basée sur (i) la caractérisation de la dynamique épidémique pour estimer ses paramètres clés, (ii) l'utilisation d’un modèle spatialement explicite pour simuler la dynamique et la gestion de cette maladie et (iii) l'utilisation de méthodes d'optimisation numérique pour identifier des stratégies de gestion efficaces. Ici, nous appliquons cette approche à la sharka, causée par le Plum pox virus. Cette maladie a un impact mondial sur la filière Prunus et est associée à d'importants coûts de gestion dans de nombreux pays. En France, la stratégie de gestion de cette maladie repose notamment sur la surveillance des vergers, l’arrachage des arbres pouvant contribuer à la propagation de l’épidémie, et des restrictions de plantation.Ma thèse indique que certaines stratégies devraient être plus rentables que celle actuellement appliquée en France. Ces stratégies nécessitent moins de surveillance des vergers et n’imposent aucune restriction de plantation. Il s'avère que certaines de ces stratégies sont efficaces pour tous les types de paysage testés, ce qui peut être intéressant en pratique pour les gestionnaires du risque. Cette approche a été appliquée à la sharka, mais elle pourrait être transposée pour optimiser la gestion d’autres épidémies.

Emerging animal diseases, zoonotic diseases and the development of international trade have led to an increase in the need for efficient animal health surveillance systems. However, the current economic environment led to significant budget cuts, resulting in a reallocation of resources dedicated to surveillance. In this context, regular evaluation of surveillance systems, on which are based the health decisions, is essential to ensure their operation, the quality of the collected data and to allow their improvement.This study focused on the evaluation of a complex surveillance system, the Sylvatub network for the surveillance of Mycobacterium bovis infection in wildlife, which consists of several surveillance components focusing on several wild species. We have used four evaluation methods: (i) a quantitative method to estimate the surveillance sensitivity by scenario trees modelling, (ii) a quantitative method to estimate the surveillance costs, enabling the estimation of a cost-effectiveness ratio, (iii) a semi-quantitative method to estimate the global operation of the system, and (iv) a qualitative method to investigate the acceptability of the surveillance. This study allowed to assess the Sylvatub network in its environmental and economical context, with the integration of behavioral and social factors; and allowed the development of recommendations for the evolution of the surveillance system and its improvement.This study has highlighted the methodological and operational advantages of the complementary use of several methods for the evaluation of complex surveillance systems. It provides methodological perspectives to support the integration of evaluation methods. The assessment of the Sylvatub system should be deepened and complemented by the evaluation of the surveillance system in cattle to explore interconnections between domestic and wild populations in this particular multi-host system.; Les maladies animales émergentes, les maladies zoonotiques et le développement du commerce international ont conduit à une augmentation des besoins en systèmes de surveillance en santé animale performants. Toutefois, le contexte économique actuel conduit à des restrictions budgétaires importantes, induisant une diminution des ressources allouées à la surveillance. Dans ce contexte, l’évaluation régulière des dispositifs de surveillance, sur lesquels sont fondées les décisions sanitaires, est indispensable afin de vérifier leur bon fonctionnement, la qualité des données collectées, et permettre leur amélioration.Notre travail a porté sur l’évaluation d’un dispositif de surveillance complexe, Sylvatub, le dispositif de surveillance de l’infection à Mycobacterium bovis dans la faune sauvage, constitué de plusieurs composantes de surveillance et ciblant plusieurs espèces sauvages. Nous avons appliqué quatre méthodes d’évaluation : (i) une méthode quantitative d’estimation de la sensibilité de la surveillance par arbres de scénarios, (ii) une méthode quantitative d’estimation des coûts de la surveillance, permettant le calcul d’un ratio coût-efficacité, (iii) une méthode semi-quantitative permettant l’étude du fonctionnement général du dispositif et (iv) une méthode qualitative permettant d’investiguer l’acceptabilité de la surveillance. Ces travaux ont permis d’évaluer le dispositif Sylvatub dans son contexte environnemental et économique, en intégrant des facteurs comportementaux et sociaux, et ont permis la formulation de recommandations pour l’évolution du dispositif et son amélioration.Ces travaux ont également permis de souligner les avantages méthodologiques et opérationnels de l’utilisation complémentaire de plusieurs méthodes pour l’évaluation de dispositifs de surveillance complexes et proposent des perspectives méthodologiques pour favoriser l’intégration des méthodes d’évaluation. L’évaluation du dispositif Sylvatub devra être poursuivie et complétée par celle du dispositif de surveillance en élevage bovin afin d’étudier les interconnexions entre les populations domestiques et sauvages dans ce système multi-hôtes particulier.