Is AI the answer to predicting how future diseases will spread?

Embargoed until: Publicly released: 2025-02-20 03:00

Australia; International; NSW

CC-0. https://pixabay.com/photos/source-code-software-computer-4280758/

International scientists, including an Australian, say artificial intelligence (AI) has the potential to transform infectious disease epidemiology, the study of how diseases spread. The experts outline how recent advances in AI could help answer key questions and discuss existing AI methods that could be applied to routinely collected infectious disease surveillance data. They also consider the social context of using AI for epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, they identify some of the limitations of current AIs for tackling epidemiology, including their inability to explain reasoning, the fact that most existing models are limited to text or voice outputs, and their ownership by big tech companies which spend huge sums on training AIs and choose when and how to release new iterations. Waiting for new AI deployment to then fine-tune them to answer epidemiological questions may not be sustainable or equitable, the authors conclude.

Attachments

Note: Not all attachments are visible to the general public. Research URLs will go live after the embargo ends.

Research Springer Nature, Web page The URL will go live after the embargo ends

Journal/
conference: Nature

Research:Paper

Organisation/s: The University of Sydney, University of Copenhagen, Denmark

Funder: M.U.G.K. acknowledges funding from The Rockefeller Foundation (PC-2022-POP-005), Google.org, the Oxford Martin School Programmes in Pandemic Genomics and Digital Pandemic Preparedness (also C.F. and L.F.), European Union’s Horizon Europe programme projects MOOD (874850) and E4Warning (101086640), the John Fell Fund, a Branco Weiss Fellowship, Wellcome Trust grants 303666/Z/23/Z, 226052/Z/22/Z and 228186/Z/23/Z (also H.T.), United Kingdom Research and Innovation (APP8583) and the Medical Research Foundation (MRF-RG-ICCH-2022-100069, also H.T.), UK International Development (301542-403), the Bill & Melinda Gates Foundation (INV-063472) and Novo Nordisk Foundation (NNF24OC0094346, also H.T.); E.C.H. from a National Health and Medical Research Council (NHMRC) Investigator award and by AIR@InnoHK administered by the Innovation and Technology Commission, Hong Kong Special Administrative Region, China; and S. Bhatt from the MRC Centre for Global Infectious Disease Analysis (reference MR/ X020258/1), funded by the UK Medical Research Council (MRC). This UK funded award is carried out in the framework of the Global Health EDCTP3 Joint Undertaking. S. Bhatt is funded by the National Institute for Health and Care Research (NIHR) Health Protection Research Unit in Modelling and Health Economics, a partnership between UK Health Security Agency, Imperial College London and LSHTM (grant code NIHR200908). S. Bhatt acknowledges support from the Novo Nordisk Foundation through The Novo Nordisk Young Investigator Award (NNF20OC0059309). S. Bhatt acknowledges the Danish National Research Foundation (DNRF160) through the chair grant, which also supports N. Scheidwasser, M.P.K. and J.L.C.-S. S. Bhatt acknowledges support from The Eric and Wendy Schmidt Fund For Strategic Innovation through the Schmidt Polymath Award (G-22-63345). O.R. acknowledges funding support from the Bill & Melinda Gates Foundation (OPP117509, OPP1084362), EPSRC (EP/X038440/1), NIH (R01AI155080) and the Moderna Charitable Foundation; and E.J.T. from the US National Institutes of Health grant UM1TR004407. M.A.S. is supported in part through the US National Institutes of Health grants R01 AI153044 and R01 AI162611. E.S. acknowledges support in part by the AI2050 program at Schmidt Futures (grant G-22-64476). S. Bajaj is supported by the Clarendon Scholarship and St Edmund Hall College, University of Oxford and NERC DTP (grant number NE/S007474/1). T.S. acknowledges funding of ETH Zürich; F.D. from the NIH U24ES035309; C.F. from the Moh Family Foundation; M.G.-R. from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 945719); D.A.D. from the Novo Nordisk Foundation through The Novo Nordisk Data Science Emerging Investigator Award (NNF23OC0084647); and S.F. and M.Z. from the Engineering and Physical Sciences Research Council (EP/V002910/2). J.L.-H.T. is supported by a Yeotown Scholarship from New College, University of Oxford. M.J.P.’s research on infectious disease ethics is supported by the Moh Family Foundation and Wellcome (221719). B.S. acknowledge funding by the Machine Learning Cluster of Excellence, EXC number 2064/1. H.T. acknowledges support to CERI from grants from the South African Medical Research Council (SAMRC) with funds received from the National Department of Health, the Rockefeller Foundation (HTH 017), the Abbott Pandemic Defense Coalition (APDC), the National Institute of Health USA (U01 AI151698) for the United World Antivirus Research Network (UWARN), the INFORM Africa project through IHVN (U54 TW012041) and the eLwazi Open Data Science Platform and Coordinating Center (U2CEB032224), the SAMRC South African mRNA Vaccine Consortium (SAMVAC), the European Union supported by the Global Health EDCTP3 Joint Undertaking and its members, the European Union’s Horizon Europe Research and Innovation Programme (101046041), the Health Emergency Preparedness and Response Umbrella Program (HEPR Program), managed by the World Bank Group (TF0B8412), the GIZ commissioned by the Government of the Federal Republic of Germany, the UK’s Medical Research Foundation (MRF-RG-ICCH-2022-100069) and the Wellcome Trust for the Global.health project (228186/Z/23/Z). C.M. is supported by a studentship from the UK’s Engineering and Physical Sciences Research Council; and C.A.D. by the UK National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections in partnership with Public Health England (grant number: HPRU200907).

Media Contact/s

Contact details are only visible to registered journalists.