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James Hay
Research Fellow at the Pandemic Sciences Institute, University of Oxford. Using maths and stats to understand infectious disease dynamics, mostly viral kinetics and serology. https://hay-idd.github.io/






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It was absolutely wonderful to write something again with @skissler.bsky.social, @danlarremore.bsky.social and Aishani Aatresh. Here's our new review/perspective on the value of measuring and modelling viral kinetics as part of routine surveillance: royalsocietypublishing.org/rstb/article...
Delighted to share the (preprint) output of @mhairijan.bsky.social's Oxford visit: SARS-CoV-2 Neutralising Antibody Profiles Reveal Variant Specific Antibody Dynamics and Regional Differences in Infection Histories in Malawi. dx.doi.org/10.2139/ssrn...
1mo
The final piece of my PhD work is now published in Science Translational Medicine! We present a new framework to jointly infer epidemiological and antigenic parameters from multi-pathogen population serological studies🦠 www.science.org/stoken/autho...
2mo
6mo
Random time-shift approximation enables hierarchical Bayesian inference of mechanistic within-host viral dynamics models on large datasets journals.plos.org/ploscompbiol...
Abstract. Viral kinetics provide crucial insights into the biology and epidemiology of infections, with direct implications for basic science, therapeutics
royalsocietypublishing.org
Integrating viral kinetics into routine outbreak surveillance: challenges, opportunities and lessons from COVID-19
6mo
James Hay
James Hay
Background: Serological data provide important insights into SARS-CoV-2 transmission and immunity, particularly in regions with limited routine surveillance suc
ssrn.com
SARS-CoV-2 Neutralising Antibody Profiles Reveal Variant Specific Antibody Dynamics and Regional Differences in Infection Histories in Malawi
🧵 Is it a super flu year? Who knows, but I think the current reporting is stupid. A pissed off thread using data. Firstly - here are today's headlines and some from the last 3 years... spot the difference. 1/10
Author summary Understanding how viruses reproduce within an infected host is crucial for predicting disease progression and evaluating treatments. One way to study this is by using mathematical model...
Random time-shift approximation enables hierarchical Bayesian inference of mechanistic within-host viral dynamics models on large datasets
journals.plos.org
WHO Disease Update Notification: Seasonal influenza 🦠Since August 2025, there's been a rapid increase of A(H3N2) J.2.4.1 subclade K driving early & prolonged seasons 🦠Vaccine helps against hospitalisation, unclear about milder impact 🦠K induces "normal" disease spectrum www.who.int/emergencies/...
6mo
6mo
Seasonal influenza - Global situation
Seasonal influenza (‘the flu’) is an acute respiratory infection caused by influenza viruses that circulate globally and year-round. It can cause illness ranging from mild to severe, sometimes resulti...
www.who.int
Great take. We looked at the data a few weeks ago and concluded that other than starting early, this year's dynamics are comparable to previous bad seasons. Our scenario models suggest a peak in infections (not hospitalisations which lag 1/2 weeks) in early/mid December. zenodo.org/records/1770...
NetScience
6mo
Prof Christina Pagel
Had a wonderful time in Oxford this week filled with data modelling, presentations, meetings, and beautiful lunch spots! Huge thanks to @jameshay.bsky.social for inviting me down and all the wonderful researchers who have taken the time to speak with me #PhD #BigData @ox.ac.uk
Ian M. Mackay, PhD (he/him) 🦠🤧🧬📑🦟🧀
Mar 28, 2025
James Hay
Key findings England is currently experiencing a high growth rate of infections caused by the influenza A/H3N2 K clade. Antigenic change from the previously dominant clade, a rapid selective sweep evi...
zenodo.org
Evaluation of the epidemiological outlook of the influenza A/H3N2 clade K in England during the 2025-26 season
🧵 Is it a super flu year? Who knows, but I think the current reporting is stupid. A pissed off thread using data. Firstly - here are today's headlines and some from the last 3 years... spot the difference. 1/10
Mhairi McCormack
6mo
Prof Christina Pagel
Megan O'Driscoll