James Hay is a research fellow at the Pandemic Sciences Institute at the University of Oxford funded through a Wellcome Trust Early Career Award. His expertise is in infectious disease epidemiology and mathematical modelling, with a particular interest in using pathogen and host biomarker data (e.g., serology) to understand and track the dynamics of infectious diseases. His current research focuses on integrating quantitative virological and immunological data into models of epidemic dynamics to improve infectious disease surveillance and vaccine evaluation. His publications, review history and awards are listed on Google Scholar and ORCID.

James completed his PhD at Imperial College in 2019 and spent three years as a postdoc at the Harvard Chan School of Public Health. Before that, his undergraduate degree was in Natural Sciences (Zoology) at the University of Cambridge, followed by an MSc in Computing Science at Imperial College.

I’m always happy to talk about infectious disease dynamics (influenza is my favourite pathogen), serology, viral kinetics, inference methods, hiking, squash… or anything else! Feel free to get in touch at james.hay@ndm.ox.ac.uk.

News & updates

2026

  • 2026-03-17: Punya Alahakoon will be giving a talk at the 2nd Bonn Conference on Mathematical Life Sciences presenting our work on “Enhancing epidemiological parameter inference using quantitative diagnostic data”.
  • 2026-03-09: New preprint led by Kath O’Reilly at LSHTM with contributions from the group using serosolver. Our new study reconstructs early-life norovirus infection histories from antibody data in English children, revealing how immune responses are shaped by the first variants encountered.

2025

  • 2025-12-17: James was interviewed on BBC Radio 4’s More or Less discussing the 2025/26 influenza season.
  • 2025-12-12: What is super flu? A new article in The Conversation explaining how this year’s influenza season differs, or does not differ, to previous years.
  • 2025-12-10: Paper published in Nature Communications led by Samantha Bents. Multiplex serology across respiratory viruses reveals age-specific immune dynamics after COVID-19, helping explain unusual post-pandemic epidemic patterns.
  • 2025-11-24: New preprint: is this year’s influenza season really unprecedented? Using past and current surveillance data from the UKHSA, we compare this season’s influenza growth rates to past years, finding that peak growth rates of cases from the 2025/26 season have been in line with previous bad seasons. We also present scenario analyses finding that dynamics are consistent with partial immune escape or an earlier seed date, with both scenarios pointing to an early-to-mid December peak.
  • 2025-11-19: Paper published in Nature Communications: new work on nowcasting epidemic trends using routine virologic testing data. This builds on earlier work using viral load distributions to infer epidemic growth rates.
  • 2025-11-17: Welcome to Bienfait Igiraneza and Alex Greenshields-Watson. Bienfait and Alex are new postdocs in the group using machine learning and modelling to understand the early immune response to ChAdOx Nipah vaccination in collaboration with the Gilbert group.
  • 2025-10-31: James was a keynote speaker at The Swiss Meeting for Infectious Disease Dynamics (SMIDDY2025). His talk title was “A quantitative world: should we stop binarizing our epidemiological data?”.
  • 2025-10-16: Presented our ongoing project “A statistical framework to disentangle the effect of exposure history on correlates of protection” at the 4th Correlates of Protection for Next Generation Influenza Vaccines meeting. Many thanks to the conference organisers for awarding me an ECR scholarship to attend the meeting!
  • 2025-10-13: Welcome to Ben Hollingdale who is starting his DPhil jointly supervised by James and Lisa Stockdale. Ben’s research investigates the impact of the R21 vaccine on long-term infection rates, antibody dynamics and immunity to malaria through childhood.
  • 2025-09-08: New preprint led by David Hodgson on estimating hidden infections using longitudinal serology: we introduce serojump, a probabilistic framework that reconstructs infection timing and antibody kinetics from individual-level serological data, revealing infections missed by standard threshold-based methods.
  • 2025-07-24: New preprint led by Yan Wang on RSV serology. We developed a Bayesian framework that improves estimation of neutralising antibody titres from dilution-series assays, enabling more accurate measurements of population immunity and vaccine responses.
  • 2025-07-05: New preprint led by Punya Alahakoon using viral load measurements from mosquito traps to track West Nile virus transmission dynamics (in collaboration with Joseph Fauver at the University of Nebraska).
  • 2025-06-01: Paper published in PLOS Computational Biology led by Vania Lin at HKU on using RT-qPCR cycle threshold values to estimate epidemiological dynamics under different surveillance settings.
  • 2025-05-15: Paper published in American Journal of Epidemiology led by Arthur Menezes at Princeton, analysing long-term measles immunity dynamics in Madagascar using serological data and modelling.
  • 2025-04-10: Paper published in Epidemics led by James Petrie exploring how improved testing strategies could strengthen defence against future respiratory virus pandemics.

2024

  • 2024-12-07: Check out our new review article in Epidemics giving a full primer and overview of modelling methods for estimating infections and epidemic dynamics using serological data. With Saki Takahashi at JHU and Isobel Routledge at UCSF.
  • 2024-11-07: Reconstructed influenza A/H3N2 infection histories using multistrain serology, paper out in PLOS Biology! We inferred lifetime infections and antibody levels for 1130 individuals in Guangzhou, China, giving insights into long-term influenza incidence and immunity. Bsky thread here.
  • 2024-09-25: Presented work on influenza immune landscapes at the Options XII conference (best poster award in Public Health and Policy).