ABSTRACT
Maintaining vigilance with regard to the introduction of exotic diseases is a challenge, particularly because these diseases are numerous, some are not well known, and they are not immediately suspected by people in day-to-day practice, specifically veterinary practitioners. The objective of this article is to present a tool to support the identification of suspect cases of exotic diseases in cattle, based on a Bayesian approach. A list of 22 exotic diseases in mainland France was selected mainly on the basis of their potential consequences if introduced, and the ability to detect them on a clinical basis. In response of a set of epidemio-clinical criteria observed in the field this tool provides a list of exotic diseases by descending order of likelihood. The tool's performance was assessed by simulation. When simulating epidemio-clinical observations of each of the 22 diseases included in the tool with some uncertainty, the right disease was ranked in the first place between 83.8% and 100% of the times, and always in the five most likely diseases. Even when some noise was introduced in the epidemio-clinical observations simulated by addition of criteria non-characteristic of the simulated diseases, the right disease was always in the five most likely diseases. This tool could be usefully included in a global approach aiming to improve vigilance against exotic diseases.
