Monitoring infectious diseases is essential for safeguarding equine health and ensuring the sustainability of the horse industry. In 2019, the Royal Veterinary Association of the Netherlands (KNMvD) and Royal GD (GD Animal Health) launched SEIN (Surveillance of Equine Infectious diseases in the Netherlands), a voluntary surveillance system for laboratory-confirmed outbreaks of equid alphaherpesvirus 1 (EHV-1), equid alphaherpesvirus 4 (EHV-4), equine influenza virus (EIV), and Streptococcus equi subsp. equi. This retrospective study analyzed 364 confirmed outbreaks reported through SEIN between June 2019 and April 2023. S. equi was the most commonly reported pathogen overall (64%). Among outbreaks involving respiratory disease, S. equi accounted for 74% of cases, followed by EHV-4 (16%), EIV (6%), and EHV-1 (4%). The geographical distribution of outbreaks covered 80 of the 90 postal code regions (89%), and approximately half of all participating practices generated at least 1 alert. Vaccination data revealed low coverage against EHV-1/4, EIV, and S. equi among both affected horses and premises. Clinical signs overlapped between pathogens, but some were more pathogen-specific, e.g., coughing in EIV, and abscessation in S. equi. The SEIN system provided spatiotemporal information on confirmed outbreaks. These results underscore the importance of quick diagnostics and structured surveillance systems in guiding prevention strategies.

Optimising kid rearing is essential for sustainable dairy goat farming, yet validated parameters and practical benchmark data are lacking. This study aimed to develop and evaluate a set of key performance indicators (KPIs) for monitoring kid-rearing practices through a participatory approach. Researchers, veterinarians and five dairy goat farms participated developed a prototype set of KPIs covering birth, colostrum management, average daily gain (ADG), and mortality, which were stratified across four rearing phases: perinatal (first 48 h), postnatal (birth to weaning), postweaning (weaning to 12 weeks), and final rearing (12 weeks to mating). The set of KPIs was subsequently tested for its added value but also for its feasibility in practice on the five participating farms as proof of principle. On these farms, data were gathered over a six-month period (June 2020–January 2021), combining routine census data with on-farm records. Only three out of five farms returned complete datasets encompassing data from 715 kids. Results revealed significant variation in rearing outcomes across farms, particularly in birth weights and postweaning growth. Birth weight emerged as a key predictor for ADG, while differences in weaning strategies had the greatest impact on postweaning performance. Although the farmers acknowledged the added value of the developed KPIs, collection of these data during the kidding season was challenging and required further automation to simplify data collection on the farm. This study demonstrates the feasibility and value of individual-level data collection in dairy goat systems and underscores the need for practical tools to support routine monitoring and data-driven management.