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Artificial intelligence for modelling infectious disease epidemics

Author

Listed:
  • Moritz U. G. Kraemer

    (University of Oxford
    University of Oxford)

  • Joseph L.-H. Tsui

    (University of Oxford
    University of Oxford)

  • Serina Y. Chang

    (University of California Berkeley
    UCSF UC Berkeley Joint Program in Computational Precision Health)

  • Spyros Lytras

    (The University of Tokyo)

  • Mark P. Khurana

    (University of Copenhagen)

  • Samantha Vanderslott

    (University of Oxford
    University of Oxford and NIHR Oxford Biomedical Research Centre)

  • Sumali Bajaj

    (University of Oxford)

  • Neil Scheidwasser

    (University of Copenhagen)

  • Jacob Liam Curran-Sebastian

    (University of Copenhagen)

  • Elizaveta Semenova

    (Imperial College London)

  • Mengyan Zhang

    (University of Oxford)

  • H. Juliette T. Unwin

    (University of Bristol)

  • Oliver J. Watson

    (Imperial College London)

  • Cathal Mills

    (University of Oxford
    University of Oxford)

  • Abhishek Dasgupta

    (University of Oxford
    University of Oxford)

  • Luca Ferretti

    (University of Oxford)

  • Samuel V. Scarpino

    (Northeastern University
    Santa Fe Institute)

  • Etien Koua

    (World Health Organization Regional Office for Africa)

  • Oliver Morgan

    (World Health Organization)

  • Houriiyah Tegally

    (Stellenbosch University)

  • Ulrich Paquet

    (Muizenberg)

  • Loukas Moutsianas

    (Genomics England)

  • Christophe Fraser

    (University of Oxford)

  • Neil M. Ferguson

    (Imperial College London)

  • Eric J. Topol

    (Scripps Research)

  • David A. Duchêne

    (University of Copenhagen)

  • Tanja Stadler

    (ETH Zürich
    Swiss Institute of Bioinformatics)

  • Patricia Kingori

    (University of Oxford)

  • Michael J. Parker

    (University of Oxford
    University of Oxford)

  • Francesca Dominici

    (Harvard T.H. Chan School of Public Health)

  • Nigel Shadbolt

    (University of Oxford
    The Open Data Institute)

  • Marc A. Suchard

    (Los Angeles)

  • Oliver Ratmann

    (Imperial College London
    Imperial College)

  • Seth Flaxman

    (University of Oxford)

  • Edward C. Holmes

    (The University of Sydney)

  • Manuel Gomez-Rodriguez

    (Max Planck Institute for Software Systems)

  • Bernhard Schölkopf

    (Max Planck Institute for Intelligent Systems and ELLIS Institute Tübingen)

  • Christl A. Donnelly

    (University of Oxford
    University of Oxford)

  • Oliver G. Pybus

    (University of Oxford
    University of Oxford
    The Royal Veterinary College)

  • Simon Cauchemez

    (Institut Pasteur, Université Paris Cité, U1332 INSERM, UMR2000 CNRS)

  • Samir Bhatt

    (University of Copenhagen
    Imperial College London
    Pioneer Centre for Artificial Intelligence University of Copenhagen)

Abstract

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI.

Suggested Citation

  • Moritz U. G. Kraemer & Joseph L.-H. Tsui & Serina Y. Chang & Spyros Lytras & Mark P. Khurana & Samantha Vanderslott & Sumali Bajaj & Neil Scheidwasser & Jacob Liam Curran-Sebastian & Elizaveta Semenov, 2025. "Artificial intelligence for modelling infectious disease epidemics," Nature, Nature, vol. 638(8051), pages 623-635, February.
    • Handle: RePEc:nat:nature:v:638:y:2025:i:8051:d:10.1038_s41586-024-08564-w
    DOI: 10.1038/s41586-024-08564-w
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