Integrating Multiple Data Sources and Artificial Intelligence for Early Detection of Epidemiological Problems: A One Health Perspective
The growing complexity of global health challenges, including zoonotic diseases, climate change, and urbanization, demands innovative and interdisciplinary approaches to epidemiological surveillance. The One Health approach, which emphasizes the interconnectedness of human, animal, and environmental health, provides a holistic lens for understanding and addressing the root causes of disease outbreaks and environmental health risks. AI techniques, such as machine learning and predictive modelling, enhance the ability to process large-scale, heterogeneous datasets, iden