Search

Additional file 1.

International audience; 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 international community and governmental organizations are actively calling for the implementation of One Health (OH) surveillance systems to target health hazards that involve humans, animals, and their environment. In our view, the main characteristic of a OH surveillance system is the collaboration across institutions and disciplines operating within the different sectors to plan, coordinate, and implement the surveillance process. However, the multisectoral organizational models and possible collaborative modalities implemented throughout the surveillance process are multi-fold and depend on the objective and context of the surveillance. The purpose of this study is to define a matrix to evaluate the quality and appropriateness of multisectoral collaboration through an in-depth analysis of its organization, implementation, and functions. We developed a first list of evaluation attributes based on (i) the characteristics of the organization, implementation, and functionality of multisectoral surveillance systems; and (ii) the existing attributes for the evaluation of health surveillance systems and OH initiatives. These attributes were submitted to two rounds of expert-opinion elicitation for review and validation. The final list of attributes consisted of 23 organizational attributes and 9 functional attributes, to which 3 organizational indexes were added measuring the overall organization of collaboration. We then defined 75 criteria to evaluate the level of satisfaction for the attributes and indexes. The criteria were scored following a four-tiered scoring grid. Graphical representations allowed for an easy overview of the evaluation results for both attributes and indexes. This evaluation matrix is the first to allow an in-depth analysis of collaboration in a multisectoral surveillance system and is the preliminary step toward the creation of a fully standalone tool for the evaluation of collaboration. After its practical application and adaptability to different contexts are field-tested, this tool could be very useful in identifying the strengths and weaknesses of collaboration occurring in a multisectoral surveillance system.

The international community and governmental organizations are actively calling for the implementation of One Health (OH) surveillance systems to target health hazards that involve humans, animals, and their environment. In our view, the main characteristic of a OH surveillance system is the collaboration across institutions and disciplines operating within the different sectors to plan, coordinate, and implement the surveillance process. However, the multisectoral organizational models and possible collaborative modalities implemented throughout the surveillance process are multi-fold and depend on the objective and context of the surveillance. The purpose of this study is to define a matrix to evaluate the quality and appropriateness of multisectoral collaboration through an in-depth analysis of its organization, implementation, and functions. We developed a first list of evaluation attributes based on (i) the characteristics of the organization, implementation, and functionality of multisectoral surveillance systems; and (ii) the existing attributes for the evaluation of health surveillance systems and OH initiatives. These attributes were submitted to two rounds of expert-opinion elicitation for review and validation. The final list of attributes consisted of 23 organizational attributes and 9 functional attributes, to which 3 organizational indexes were added measuring the overall organization of collaboration. We then defined 75 criteria to evaluate the level of satisfaction for the attributes and indexes. The criteria were scored following a four-tiered scoring grid. Graphical representations allowed for an easy overview of the evaluation results for both attributes and indexes. This evaluation matrix is the first to allow an in-depth analysis of collaboration in a multisectoral surveillance system and is the preliminary step toward the creation of a fully standalone tool for the evaluation of collaboration. After its practical application and adaptability to different contexts are field-tested, this tool could be very useful in identifying the strengths and weaknesses of collaboration occurring in a multisectoral surveillance system.

National audience

National audience

National audience

Depuis 2014, de nombreux foyers de fièvre catarrhale ovine (FCO) sont déclarés en Europe chaque année, principalement de sérotype 4, mais aussi de sérotype 1 (Italie, Croatie, Espagne, Portugal) et de sérotype 8 (France, Chypre, Suisse). On observe une diminution du nombre de foyers de FCO-1 depuis 2014, ainsi qu'une augmentation du nombre de foyers de FCO-4 et, depuis 2015, de FCO-8. L'année 2017 a été marquée par une importante épizootie de sérotype 4 qui a frappé la Sardaigne et la Corse de fin juin à décembre 2017 et l'introduction de ce sérotype 4 en France continentale. Le sérotype 2 a été identifié en Italie en 2014, le sérotype 3 a été détecté pour la première fois en Europe en Sicile en 2017, et le sérotype 16 a été signalé à Chypre en 2014, puis en Grèce et en Turquie à partir de septembre 2017. La situation épidémiologique de la FCO en Europe est donc complexe et le maintien d'un niveau de vigilance élevé est nécessaire car le changement climatique, l'évolution des aires de distribution des insectes vecteurs et les mouvements d'animaux constituent des facteurs de risque d'introduction de nouveaux sérotypes en Europe.

Les systèmes de surveillance épidémiologique reposent sur des réseaux d'acteurs qui échangent des informations de manière multidirectionnelle. Les facteurs socio-économiques influençant leur prise de décision à transmettre ou non une information doivent être pris en considération, notamment dans le cadre de l'évaluation. La méthode AccePT (Acceptability Participatory Toolkit), fondée sur des approches participatives, a été développée pour estimer l'acceptabilité des systèmes de surveillance en prenant en considération la confiance des acteurs, l'acceptabilité de l'objectif du dispositif et de son fonctionnement. Elle repose sur la mise en place de trois outils au cours d'entretiens ouverts avec des représentants de l'ensemble des acteurs impliqués dans le dispositif. Cette méthode permet de formuler des recommandations fondée ssur le contexte et prenant en considération les perceptions, attentes et besoins des différents acteurs.

The spatial and temporal study of the spread of emerging infectious diseases is crucial to understand their epidemiology and evaluate the risk of introduction into disease-free areas. In this paper, we present a generic method that models the spread rate of emerging infectious diseases that we applied to Lumpy Skin Disease (LSD), a current epizooty affecting cattle in the Balkans, from May 2015 to July 2016. In the study period, 824 outbreaks of LSD were reported in eight countries. Hotspots of viral transmission were identified mainly south of the Turkish/Greek border, southwest of Bulgaria and south of the Serbian/Bulgarian border. By using Thin Plate Spline Regression (TPSR) to interpolate the week of first invasion, we estimated the spread rate based on the mean duration of time for the infection to spread across a given area (1km). The median spread rate was 7.8km per week, with an interquartile interval of 4.6 to 13.7km and a maximum value reaching 375.6km. The distribution of spread rate indicates two diffusion processes: a localised diffusion covering small distances and suggesting vector transmission, and a diffusion at greater distances possibly due to anthropogenic movement of infected animals. Further research should focus on identifying environmental and socio-economic factors that might influence the spread of LSD to better understand the disease epidemiology and suggest targeted control measures.

Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed.

La dermatose nodulaire contagieuse des bovins (DNCB), maladie virale enzootique en Afrique sub-saharienne et classée comme danger sanitaire de catégorie I, a été détectée pour la première fois en Turquie en novembre 2013. Elle s'est ensuite étendue à l'Europe : tout d'abord dans la partie européenne de la Turquie en mai 2015, puis dans les Balkans. Au 31 juillet 2016, elle touchait la Grèce, la Bulgarie, la Macédoine (ARYM), le Monténégro, l'Albanie et la Serbie, avec 747 foyers notifiés au total. La diffusion du virus se poursuit depuis son introduction en Europe, malgré les mesures de lutte mises en place dans les pays touchés (restrictions de mouvements, abattages, vaccinations…). La vigilance quant à la diffusion de l'infection en Europe ainsi que les propositions de mise en oeuvre d'une surveillance dédiée sur le territoire national s'exercent dans le cadre de la Plateforme ESA. Cet article fait le point sur la situation épidémiologique de la DNCB dans les Balkans et propose une synthèse des connaissances épidémio-cliniques sur cette maladie.

La veille en santé animale, et notamment la détection précoce d'émergences au niveau mondial d'agents pathogènes, est l'un des moyens permettant de prévenir l'introduction en France de dangers sanitaires (Paquet et al., 2006). Cet article présente une plateforme dédiée à la collecte de données (dépêches) utiles pour la veille automatique. Le recueil des dépêches s'appuie sur des requêtes constituées de mots-clés de maladies, d'hôtes et de symptômes appliquées à Google News. Une interface Web a été développée pour consulter les articles collectés et paramétrer le processus de recueil en définissant de nouvelles combinaisons de mots-clés.

Timeliness and precision for detection of infectious animal disease outbreaks from the information published on the web is crucial for prevention against their spread. We propose a generic method to enrich and extend the use of different expressions as queries in order to improve the acquisition of relevant disease related pages on the web. Our method combines a text mining approach to extract terms from corpora of relevant disease outbreak documents, and domain expert elicitation (Delphi method) to propose expressions and to select relevant combinations between terms obtained with text mining. In this paper we evaluated the performance as queries of a number of expressions obtained with text mining and validated by a domain expert and expressions proposed by a panel of 21 domain experts. We used African swine fever as an infectious animal disease model. The expressions obtained with text mining outperformed as queries the expressions proposed by domain experts. However, domain experts proposed expressions not extracted automatically. Our method is simple to conduct and flexible to adapt to any other animal infectious disease and even in the public health domain.

La veille en santé animale, et notamment la détection précoce d'émergences au niveau mondial d'agents pathogènes, est l'un des moyens permettant de prévenir l'introduction en France de dangers sanitaires (Paquet et al., 2006). Dans ce contexte, cet article présente une plateforme dédiée à la veille automatique allant du recueil des données textuelles (dépêches) jusqu'à la restitution synthétique des informations extraites.