摘要
Census and disposal data provide a multipurpose source of information on cattle mortality. The retrospective analyses we conducted on the data gathered in the National Cattle Register produced relevant information for describing and modelling the cattle mortality baseline and evaluating the impact of the 2007-2008 Blue Tongue epidemic on the French cattle population. This work was conducted retrospectively but showed that monitoring cattle mortality near real time could help detecting unexpected events. We are thus currently working on a timely and automated system to monitor cadaver disposal requests received by rendering plants, thanks to a data interchange system recently implemented between the Ministry of Agriculture and the fallen stock companies. Besides technical and methodological challenges, using these data for surveillance purposes raises epidemiological questions that still need to be answered. The question remains notably as to whether an abnormal increased mortality is a sensitive and timely signal for detecting unexpected health events. It appears also very challenging to identify the most adequate surveillance scale (time, space and population) and the most adequate anomaly detection algorithms to apply when the characteristics of the signals to be detected (shape, amplitude, etc.) are not known a priori. In Human health, similar systems have not yet proven their ability to detect unexpected events earlier than classical surveillance systems currently in place, but they have already demonstrated their value for real time assessment of identified and potentially dangerous events. Combined with traditional surveillance systems, we think that monitoring routinely collected data could improve the surveillance of the animal population health. Even if not used for detection purposes, cattle mortality monitoring could be used to rapidly produce information on the impact and evolution of identified events, what would facilitate decision-making regarding management measures and improve the communication.