diermonitoring

Diermonitoring is the systematic collection, analysis, and interpretation of data related to animals or animal populations to monitor health, welfare, and population dynamics. The term is used in veterinary public health, wildlife management, and livestock production to support decision-making and early detection of problems. It covers both individual-level monitoring—such as routine health assessments and the use of wearable sensors to track movement, temperature, and activity—and population-level surveillance, such as disease reporting and trend analysis across herds or wild populations.

Data sources include veterinary records, diagnostic test results, mortality and morbidity databases, production data, sensor data from collars and other devices, and environmental measurements. Data integration and standardized coding are important for comparability across studies and regions. Methods range from active surveillance and passive reporting systems to sentinel surveillance and outbreak detection using statistical or model-based approaches. Modern diermonitoring often relies on digital platforms, cloud databases, and analytics to visualize trends and generate alerts.

Applications of diermonitoring include early disease detection and control, welfare assessment, improvement of husbandry practices, conservation planning, and regulatory compliance. In wildlife contexts, it supports population monitoring and habitat management, while in agriculture it informs breeding decisions and productivity optimization. Challenges include data privacy and ownership, data quality and representativeness, interoperability among systems, costs of data collection, and the need for skilled interpretation to avoid false alarms. See also epidemiology, animal welfare, veterinary public health, biosurveillance, and wildlife management.