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Led by the University of Oxford in partnership with the World Health Organization and an international consortium of leading research, public health and technology partners, the three-year PANDAI project will develop and deploy advanced AI models to transform the detection, assessment, prediction and response to global infectious disease threats.
Oxford, UK, September 21, 2026. The University of Oxford has been awarded an €8 million Research and Innovation grant under the European Union’s Horizon Europe programme to coordinate the development of the Pandemics AI Observatory (PANDAI). Led by Oxford’s Nuffield Department of Medicine, through its Mahidol Oxford Tropical Medicine Research Unit (MORU), and Oxford Population Health, this landmark 36-month initiative aims to strengthen capacity for timely prediction, detection, preparation for, and proportionate response to emerging pandemic threats.
Recent outbreaks of mpox, highly pathogenic avian influenza, dengue, Ebola, hantavirus and other emerging infections have highlighted the need for faster, more integrated, cross-sectoral approaches to detecting and responding to infectious disease threats across national borders.
In an era marked by shifting climate patterns and unprecedented human mobility, public health agencies face a double challenge: an overwhelming volume of fragmented data alongside a lack of predictive capabilities. Current baseline systems rely heavily on expert opinion to evaluate already reported threats, creating an acute operational delay.
The PANDAI project addresses this critical vulnerability by combining world-class multinational epidemiology expertise with artificial intelligence tools to transform a wide range of data streams into automated, actionable public health intelligence to support risk assessment and control.
At the technological core of the Observatory is the creation of one of the first Epidemiology-informed Domain-specific Foundation Models (EDFMs) for infectious disease surveillance and epidemic intelligence. Unlike general-purpose AI models, the EDFM will be developed specifically for epidemiology using large-scale multimodal datasets. It will integrate disease surveillance, environmental, health system, veterinary, preparedness capacity, mobility and pathogen genomic timely data to provide public health authorities with AI-driven insights. These insights will enable the PANDAI platform to provide earlier warning of emerging infectious disease threats, more accurate risk assessment, and evidence-based decision support for public health authorities.
Professor Richard Maude, Principal Investigator of PANDAI, Professor of Tropical Medicine at the University of Oxford and Head of Epidemiology at the Mahidol Oxford Tropical Medicine Research Unit (MORU), said:
"Public health authorities already have access to enormous amounts of information, but the challenge is turning that information into reliable intelligence quickly enough to make a difference.
"PANDAI will use AI to bring together diverse sources of data, assess what emerging threats mean for different places and populations, predict how they may develop, and provide the evidence needed to make faster and better-informed public health decisions.”
MORU’s Epidemiology team brings decades of experience in infectious disease surveillance, data science and data-driven public health decision-making, working in partnership with Ministries of Health, UN agencies and research institutions across Asia. This expertise in integrating diverse data streams into actionable public health intelligence will help underpin the development and validation of the PANDAI platform.
Reflecting the project's institutional significance, the World Health Organization (WHO) Health Security Division/Europe serves as a foundational partner. Leading the work to define what the system needs to do and how it should be structured, the WHO will ensure that the PANDAI platform integrates smoothly with existing frameworks, such as the Epidemic Intelligence from Open Sources (EIOS) initiative, and establishes direct utility for national Ministries of Health and global policymakers.
The PANDAI platform will undergo rigorous, multi-country validation across three distinct transmission pathways representing high-impact pathogens: vector-borne arboviruses (such as dengue and West Nile virus), respiratory viruses (exemplified by seasonal and novel avian/swine influenza strains like H5N1), and direct-contact infections (mpox). Validation across these complementary transmission pathways will help ensure that the platform's adaptive framework can be generalised to future emerging infectious disease threats, including the unknown ‘Disease X’. Beyond tracking, a generative synthetic population module will allow public health officials to conduct secure ‘what-if’ simulations, assessing the real-world impact of interventions, such as localised lockdowns or prioritised vaccination schedules, prior to field deployment.
Dr Marc-Alain Widdowson, World Health Organization European Region, said:
"This initiative will make a real difference to how the public health community can act on data, by bringing together far more sources and perspectives than we've had access to before. By building on existing WHO systems and expanding use of AI, we'll be able to pick out and prioritise the most important signals faster, build a fuller picture of the risk, and quickly recommend the right control measures for the situation at hand serving Member States.”
Operating within Europe’s strict legal and ethical framework, the PANDAI consortium will address the legal, ethical and societal dimensions of AI-enabled pandemic prevention, detection, and monitoring. Led by the Luxembourg National Data Service (LNDS), the project includes a dedicated compliance and ethics work package focused on fostering trustworthy AI, supporting consortium-wide compliance efforts, and promoting responsible data governance. LNDS will develop an overarching ethical framework, coordinate compliance strategy including a roadmap towards AI Act compliance, and provide ongoing guidance to partners on data protection, data governance, and regulatory matters. Through these activities, PANDAI aims to demonstrate that innovative AI solutions can be developed in a manner that respects fundamental rights, transparency, and public trust.
Professor Melinda Mills, co-investigator from Oxford Population Health, said:
"PANDAI brings together multimodal data on population behaviour, mobility, health systems and demographics to better understand how diseases spread and how people respond. By focusing on strong communication, integrating behavioural social science, attention to diversity and stakeholder perspectives into AI models from the outset, we can build tools that are not only more accurate, but also more equitable, trusted and useful for public health decision-making.”
The announcement follows the successful completion of the PANDAI consortium's inaugural in-person session, which took place at Christ Church, Oxford, on June 25–26, 2026. The workshop united epidemiologists, computer scientists, legal experts, and patient advocates to formalise system specifications and data access protocols, marking the official launch across all eight work packages.
The PANDAI project brings together nine partner organisations spanning public health, artificial intelligence, data science, technology, governance and civil society across seven countries:
- University of Oxford (United Kingdom) – Coordinator
- World Health Organization (Copenhagen)
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) (Bangladesh)
- Clalit Health Services (Israel)
- Bahia Software SLU (Spain)
- Technovative Solutions Ltd (United Kingdom)
- Arteevo Technologies Ltd (Israel)
- Luxembourg National Data Services (PNED GIE) (Luxembourg)
- Infectious Disease Alliance (Denmark)
Ends
Media enquiries
Mahidol Oxford Tropical Medicine Research Unit (MORU)
Wiraporn (Cee) Srisuwanwattana
Senior Communications Manager
Wiraporn@tropmedres.ac
Oxford Population Health
Anne Whitehouse
Director of Communications and Public Engagement
anne.whitehouse@ndph.ox.ac.uk
About the University of Oxford
The University of Oxford is a world-renowned center of learning, teaching, and research, consistently ranked among the top universities globally. Oxford’s Nuffield Department of Medicine (NDM) and Nuffield Department of Population Health (NDPH) stand at the forefront of global health research, pioneering structural insights into tropical medicine, computational epidemiology, and demographic data science to combat the world's most pressing medical and societal challenges.
About the Mahidol Oxford Tropical Medicine Research Unit (MORU)
Established in 1979, the Mahidol Oxford Tropical Medicine Research Unit (MORU) is a long-standing collaboration between Mahidol University, the University of Oxford and Wellcome. Based in Bangkok, with research networks across Asia and Africa, MORU conducts research on infectious diseases, epidemiology, clinical trials, antimicrobial resistance and global health.
About the World Health Organization/Europe
The WHO Regional Office for Europe (WHO/Europe) is one of the World Health Organization's six regional offices worldwide. Headquartered in Copenhagen, Denmark, it serves 53 member states across a vast geographic area from the Atlantic to the Pacific oceans, protecting the health of nearly one billion people.
About the Leverhulme Centre for Demographic Science (LCDS)
Established in 2019, the Leverhulme Centre for Demographic Science (LCDS) is a multidisciplinary research centre at the University of Oxford. Based in the Nuffield Department of Population Health, LCDS brings together researchers from across the social, data and health sciences to develop innovative methods and data resources that improve understanding of population change, health, ageing, migration and inequality, informing evidence-based policy and decision-making worldwide.
