AI reshapes the future of influenza prevention
AI- driven models are helping researchers predict viral mutations and improve vaccine strain selection, addressing long-standing challenges in seasonal influenza control.
Seasonal influenza remains a significant global health burden, causing millions of severe infections and significant mortality each year, according to World Health Organisation estimates released in early 2025.
In several regions, flu activity has returned to or surpassed pre-pandemic levels, placing older adults, young children, and individuals with chronic conditions at the highest risk. Such patterns reinforce the need for improved prevention strategies and more effective vaccines.
Efforts to control influenza are challenged by the virus’s rapid mutation and the limitations of traditional laboratory methods. AI and machine learning are emerging as powerful tools for predicting antigenic changes, enhancing vaccine strain selection, and accelerating manufacturing.
Beyond vaccine development, AI-driven models are enhancing infection monitoring and immune response analysis by leveraging routine clinical data. These advances enhance surveillance and pave the way for personalised influenza prevention and treatment.
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