Artículos de Revista en Ciencias Agrarias · 2026

Syndromic surveillance in slaughterhouses : A scoping review

Syndromic surveillance in slaughterhouses represents a valuable approach for early disease detection and largescale animal health monitoring. Despite its increasing application, the evidence base remains fragmented, and important methodological and terminological inconsistencies persist. This scoping review seeks to provide an integrated overview of existing systems, highlight cross-cutting patterns and limitations, identify knowledge gaps, and inform future standardization and optimization efforts in this field. Following the PRISMA-ScR guidelines, we reviewed peer-reviewed studies reporting the use of slaughterhouse-derived data for syndromic surveillance. Searches were performed in four electronic databases and major conference proceedings; proceedings were eligible for inclusion only when they had been published in indexed, peer-reviewed journals. Thirty-four studies published between 1987 and 2024 were included. Research activity has increased markedly over time but remains geographically concentrated in Europe (n = 11) and the Americas (n = 16), with pigs and cattle being the most frequently studied species. Across studies, substantial heterogeneity was observed in terms of syndromic classifications, analytical methods, and system design. Slaughterhouse-based syndromic surveillance is most commonly used for early disease detection, monitoring of animal health and welfare, and supporting epidemiological investigations. The reported strengths included broad population coverage, costeffectiveness, and feasibility within existing inspection systems. However, recurring limitations were related to data quality, reporting biases, limited validation, and poor standardization across systems. Overall, syndromic surveillance in slaughterhouses shows considerable potential as a complementary component of animal health surveillance, particularly for early warning and population-level monitoring. Advancing its effective implementation will require greater methodological harmonization, improved validation, and stronger integration with other surveillance data streams within national and international One Health frameworks.