EPI-DOM approach for comprehensive assessment of integral animal welfare

Introduction Animal welfare is a critical component of sustainable production systems, affecting ethical practices and product quality. This review aims to clarify the concept of animal welfare, particularly regarding the mental state highlighted by the World Organization for Animal Health. Methods A comprehensive literature review was conducted, focusing on studies published between 1980 and 2024. Databases used included CAB Abstracts, Scopus, PubMed, ISI Web, Scielo, Google Scholar, and specialized websites for scientific and technical information dissemination. The search incorporated keywords such as animal, sentience, consciousness, intelligence, freedoms, domains, indicators, measurement, hazard, risk factor, and management, all related to animal welfare. Results This review presents a detailed analysis of the convergence and divergence between the Five Freedoms and the Five Domains, which are widely used for assessing animal welfare. The analysis identifies gaps in addressing the complexities of animal welfare, especially regarding mental states and risk factors. Discussion This analysis introduces the EPI-DOM approach, a conceptual framework that integrates basic epidemiological concepts (EPI) with a new vision and classification of animal welfare domains (DOM). The EPI-DOM approach separates indicators measured in animals from external factors influencing their welfare, offering a more holistic evaluation that includes physical, mental, and behavioral dimensions. The framework incorporates risk factors, classified into the domains of management, environment, and interaction, making it a versatile tool for improving welfare assessment across species and production systems. Conclusion The EPI-DOM framework provides a comprehensive and adaptable model for animal welfare evaluation, with potential to enhance management practices and ethical production. Future research should focus on validating and refining EPI-DOM across different species and production environments to optimize welfare and management strategies.