Evaluation of influenza A/H3N2 epidemiology in England during the 2025-26 season
Authors/Creators
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Hay, James A
(Contact person)1
-
Alahakoon, Punya
(Researcher)1
-
Greenshields-Watson, Alexander
(Researcher)1
-
Kendall, Michelle
(Researcher)1
-
Ghafari, Mahan
(Researcher)1, 2
-
Wymant, Chris
(Researcher)1
-
Hinch, Robert
(Researcher)1
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Ferretti, Luca
(Researcher)1
-
Panovska-Griffiths, Jasmina
(Researcher)1, 3, 4
-
Fraser, Christophe
(Researcher)1
- 1. Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- 2. Department of Biology, University of Oxford, Oxford, UK
- 3. The Queen's College, University of Oxford, Oxford, UK
- 4. UK Health Security Agency, London, UK
Description
England has experienced 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 evident in genomic data, and an unusually early start to the season have raised concerns about the potential severity of this year’s influenza season. We analysed publicly available surveillance data going back to the 2011/12 season and found that the peak growth rate of influenza infections and the peak time-varying reproduction number has been largely consistent with previous severe seasons. Scenario analyses using an age-stratified compartmental model compared to the previous A/H3N2 season in 2022/23 suggest that current trends are compatible with moderate levels of immune escape in all ages, or slightly greater immune escape in children, or a 10-20% higher R0, or an earlier seed date with no change in virus fitness or immune escape. Substantial immune escape appears to be unlikely given current epidemiological trends. In almost all scenarios, an earlier and faster epidemic growth rate leads to earlier depletion of susceptibles with a dampening effect due to the half term school holiday. To support understanding and exploration of model outputs, an interactive visualisation tool was developed and made available online: https://hay-idd.shinyapps.io/ModelFluUk-H3N2/. This rapid analysis is intended to support situational awareness. It provides quantitative comparisons of early epidemic growth rates with previous seasons and qualitative insights into plausible epidemic dynamics.
Files
version2.pdf
Files
(5.3 MB)
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Additional details
Funding
- Wellcome Trust
- 225001/Z/22/Z
- Wellcome Trust
- 309152/Z/24/Z
- Wellcome Trust
- 309205/Z/24/Z
- Uczelnia Warszawska im. Marii Skłodowskiej-Curie
- 101131463 SIMBAD
- UK Research and Innovation
- EP/Y037375/1
- Coalition for Epidemic Preparedness Innovations
Dates
- Created
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2025-11-24
- Updated
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2025-12-22
Software
- Repository URL
- https://github.com/hay-idd/influenza_H3N2_k_clade
- Development Status
- Wip