From Reactive to Predictive One Health: AI-Enabled Frameworks for Integrated Zoonotic Surveillance and Governance

Area of Science:

• Public Health
• Infectious Disease Epidemiology
• Data Science

Background:

• The One Health approach, crucial for managing zoonotic diseases, faces significant challenges due to fragmented data across human, animal, and environmental sectors.
• Climate change intensifies pathogen transmission risks and agri-food system vulnerabilities, highlighting the urgent need for integrated surveillance.
• Past outbreaks like brucellosis and *Salmonella* Umbilo underscore critical weaknesses in real-time, interoperable data sharing.

Purpose of the Study:

• To propose an AI-enabled One Health Information System (OH-IS) to overcome data fragmentation.
• To outline a conceptual framework for integrating diverse data streams for enhanced zoonotic surveillance.
• To advocate for a shift from descriptive to anticipatory disease surveillance.

Main Methods:

• Conceptual framework development for an AI-enabled OH-IS.
• Integration of multi-matrix data: Earth observation, whole-genome sequencing (WGS) genomic surveillance, and livestock mobility data.
• Application of FAIR data principles and privacy-preserving architectures.

Main Results:

• Identification of key weaknesses in current data management, particularly the lack of real-time, interoperable data sharing.
• A proposed OH-IS conceptual framework integrating diverse data streams for improved risk assessment and outbreak reconstruction.
• Demonstration of how automated semantic harmonization can enhance analysis of siloed databases.

Conclusions:

• An AI-enabled OH-IS, grounded in FAIR principles, offers a scalable model for integrated, data-driven One Health surveillance.
• This approach can facilitate a transition towards anticipatory surveillance, enhancing global health security and aligning with EU digital health policies.
• Addressing data fragmentation is essential for effective operationalization of the One Health approach in the face of climate change and emerging infectious diseases.