Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SARerr model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SARerr model, which led to a trend SARerr model. Overall, BT spread from north-eastern to south-western France. The average trend SARerr-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SARerr-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SARerr models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases

Sheep Feed and Scrapie, France

Proprietary concentrates and milk replacers were linked to risk for scrapie

Qualification sanitaire des troupeaux, représentations du risque selon les acteurs et les disciplines

La qualification sanitaire vise à établir de manière objective et fiable le statut sanitaire d'un animal ou d'un ensemble d'animaux au regard d'une maladie infectieuse. Concevoir une qualification sanitaire repose sur des connaissances biologiques concernant l'agent pathogène, ses voies de transmission et les moyens de détection de la maladie. Les modèles mathématiques et les outils statistiques et probabilistes permettent d'intégrer ces connaissances tout en prenant en compte l'incertitude et la variabilité des données biologiques. Les sciences humaines apportent un éclairage sur les enjeux, les perceptions et les logiques des individus et des collectifs, afin d'étudier la demande et l'acceptabilité de la qualification sanitaire. Chaque discipline apporte ainsi son point de vue sur la notion de risque sous-jacente à la démarche de qualification. Cette approche interdisciplinaire nécessite une coconstruction de la recherche, qui doit dépasser les différences culturelles et épistémologiques entre disciplines. Elle n'obéit pas à un seul type de rationalité, scientifique ou juridico-administrative ; elle mobilise nécessairement des connaissances savantes et des savoirs empiriques et dépend de nombreuses décisions pouvant engendrer convergences ou contradictions. (Résumé d'auteur

Issues and special features of animal health research

In the rapidly changing context of research on animal health, INRA launched a collective discussion on the challenges facing the field, its distinguishing features, and synergies with biomedical research. As has been declared forcibly by the heads of WHO, FAO and OIE, the challenges facing animal health, beyond diseases transmissible to humans, are critically important and involve food security, agriculture economics, and the ensemble of economic activities associated with agriculture. There are in addition issues related to public health (zoonoses, xenobiotics, antimicrobial resistance), the environment, and animal welfare