The French population of the Eurasian lynx (Lynx lynx) is small and fragmented. Any emerging disease would endanger it even further, so disease surveillance is crucial. Currently, it relies on lynx carcass surveillance. In parallel, the Eurasian lynx population is being monitored since 1997 by a large network of observers in different regions and this trove of camera-trap images could allow for the opportunistic detection of clinical signs. Camera traps have been used for a very long time in ecology and, more recently, in epidemiology to study e.g. sarcoptic mange. However, depending on image quality, the level of detail visible in the animal's body varies. This work examines how the quality of the images relates to the ability to detect cutaneous changes and abnormal body conditions. Different factors affect image quality and the detection of changes. These include intrinsic camera parameters like the type and settings of the camera trap, extrinsic factors like the external lighting conditions or the position of the animal in relation to the camera. In our data set, clearly visible cutaneous changes were associated with a different set of factors than visible abnormal body conditions. The camera-trap conditions currently used for ecological monitoring of the lynx are very diverse and may allow for the general surveillance of abnormal health signs. However, for monitoring specific health signs, the camera settings as well as the shooting context should be optimized to ensure the best possible sensitivity and specificity of the detection.
Blin et al. (Thu,) studied this question.