From One Health Surveillance to One Health Intelligence: An Operational Framework and Maturity Model for Integrated Zoonotic Disease Preparedness

The increasing frequency and complexity of zoonotic disease outbreaks highlight the limitations of traditional surveillance systems operating within specific disciplines. Although the One Health approach provides a widely accepted framework for addressing interconnected human, animal, and environmental health threats, its practical implementation remains constrained by fragmented data systems, limited interoperability, and challenges in translating multisectoral information into timely, actionable intelligence. Advances in artificial intelligence, geospatial analytics, Earth observation, climate monitoring, genomic epidemiology, and digital health technologies provide new opportunities to strengthen integrated preparedness and anticipatory decision-making. Building on emerging international One Health Intelligence (OHI) initiatives, this perspective presents an operational framework for implementing One Health Intelligence Systems (OHIS) and proposes the One Health Intelligence Maturity Model (OHIMM) as a conceptual tool to support the progressive development and assessment of intelligence capabilities. The framework integrates multisectoral information from human, animal, wildlife, environmental, climatic, laboratory, genomic, and socioeconomic domains to support risk assessment, early warning, preparedness, and response at the human–animal–environment interface. Using West Nile Virus in Europe and Rift Valley Fever in Africa as illustrative examples, we demonstrate how existing surveillance and multidisciplinary intelligence components can be integrated to strengthen situational awareness and anticipatory public health action while discussing the governance, interoperability, and implementation challenges that remain. We argue that operationalizing OHI through structured implementation frameworks and maturity assessment can support the development of more predictive, adaptive, and resilient systems for zoonotic disease preparedness while providing a foundation for future validation and implementation research.