Advances in AI can help prepare the world for the next pandemic
A study in Nature co-authored by Tanja Stadler highlights how integrating AI into global health systems over the next five years could save lives by predicting disease outbreaks and improving healthcare resource allocation. The study emphasises the need for collaboration across academia, government, and industry to ensure AI is used ethically and effectively. While AI's potential is immense, experts caution that human oversight and high-quality data are crucial to avoid risks.

A groundbreaking study published in Nature on 19 February outlines for the first time how advances in AI can accelerate breakthroughs in infectious disease research and outbreak response.
The study – which is published following last week’s AI Action Summit and amidst increasing global debate on AI investment and regulation – puts particular emphasis on safety, accountability and ethics in the deployment and use of AI in infectious disease research.
Calling for a collaborative and transparent environment – both in terms of datasets and AI models – the study is a partnership between scientists from the University of Oxford and colleagues from academia, industry and policy organisations across Africa, America, Asia, Australia and Europe.
So far, medical applications of AI have predominantly focused on individual patient care, enhancing for example clinical diagnostics, precision medicine, or supporting clinical treatment decisions.
This review instead considers the use of AI in population health. The study finds that recent advances in AI methodologies are performing increasingly well even with limited data – a major bottleneck to date. Better performance on noisy and limited data is opening new areas for AI tools to improve health across both high-income and low-income countries.
Read on >> external page News Release of the University of Oxford.
Find original article in Nature:
Kraemer, M.U.G., Tsui, J.LH., Chang, S.Y. et al. external page Artificial intelligence for modelling infectious disease epidemics. Nature 638, 623–635 (2025). https://doi.org/10.1038/s41586-024-08564-w
This D-BSSE News is the shorted version of a external page News Release of the University of Oxford (issued on 19 February 2025).