Integrating explainable AI and One Health: a new frontier in combating infectious diseases

Infectious diseases remain a major global threat, with many emerging infections originating from animals and influenced by environmental factors, underscoring the need for a One Health approach. While machine learning is increasingly used for disease modelling and forecasting, its limited interpretability often restricts its usefulness for public health decision-making. Explainable AI (XAI) addresses this gap by making model predictions transparent and identifying key drivers of outbreaks. Integrating XAI within a One Health framework can enhance surveillance, zoonotic spillover prediction, antimicrobial resistance monitoring, and resource allocation. However, challenges such as data harmonisation, governance, privacy, and equitable access must be addressed, requiring cross-sector collaboration and continued methodological innovation.