The impact of an ageing population on pandemic risk in England

@misc{rawson2026impact,
  title = {{The impact of an ageing population on pandemic risk in England}},
  author = {T. Rawson and P. N. Perez-Guzman and E. S. Knock and C. Morgenstern and D. Valdenegro and K. A. M. Gaythorpe and L. K. Whittles and W. Hinsley and R. Sonabend and R. G. Fitzjohn and A. Cori and J. Beam Dowd and J. Bijak and N. M. Ferguson and M. C. Mills},
  howpublished = {medRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.11.26362845},
  url = {https://www.medrxiv.org/content/10.64898/2026.09.11.26362845v1},
  note = {CC BY-NC},
}

TY  - UNPB
TI  - The impact of an ageing population on pandemic risk in England
AU  - T. Rawson
AU  - P. N. Perez-Guzman
AU  - E. S. Knock
AU  - C. Morgenstern
AU  - D. Valdenegro
AU  - K. A. M. Gaythorpe
AU  - L. K. Whittles
AU  - W. Hinsley
AU  - R. Sonabend
AU  - R. G. Fitzjohn
AU  - A. Cori
AU  - J. Beam Dowd
AU  - J. Bijak
AU  - N. M. Ferguson
AU  - M. C. Mills
PY  - 2026
DA  - 2026/09/11
PB  - medRxiv
DO  - 10.64898/2026.09.11.26362845
UR  - https://www.medrxiv.org/content/10.64898/2026.09.11.26362845v1
AB  - BackgroundEnglands population is ageing rapidly, with those aged 80 years and older projected to increase 85% by 2047. Aging populations may change the dynamics of future pandemics, since older individuals face higher risks of severe outcomes and require a disproportionate share of early vaccine supply, for certain respiratory infections, despite having fewer social contacts. The net pandemic-risk implications of these competing effects cannot be resolved without dynamic transmission modelling.  MethodsWe used an age-structured stochastic SARS-CoV-2 transmission model, previously calibrated to the realtime COVID-19 epidemic across seven NHS regions of England. Running the fitted model under the ONS principal population projection for 2047 as a counterfactual, we held all non-pharmaceutical interventions fixed and scaled vaccine supply to overall population growth. Nine counterfactual scenarios spanned three vaccine deployment strategies and three ONS migration assumptions.  FindingsThe basic reproduction number remained largely unchanged by the projected age distribution. However, under the central counterfactual scenario, cumulative hospital admissions in the first two years of the pandemic were 674,004 - a 40{middle dot}3% increase over the historic baseline - and hospital deaths increased by 49{middle dot}4%, disproportionate to the 13{middle dot}9% total population increase. Trajectories were similar before the Delta variant emerged but diverged thereafter, as a larger elderly cohort delayed vaccine protection in younger, higher-contact groups. Projected burden was robust to migration assumptions (664,451-689,833 admissions). Vaccine deployment strategy had substantially greater influence, with admissions ranging from 625,859 (optimistic age-scaled deployment) to 1,193,883 (non-scaled).  InterpretationsPopulation ageing will disproportionately amplify Englands pandemic burden, driven primarily by the interaction between a growing elderly cohort and fixed age-ordered vaccine allocation, rather than by population growth alone. This vulnerability is largely independent of future migration uncertainty but is strongly modifiable through demographically-adaptive vaccine deployment planning developed before, not during, the next pandemic.  FundingMoh Family Foundation; UK Medical Research Council; Leverhulme Trust.  Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed up to June 19th, 2026, with no language restrictions using the following search terms: (COVID-19 OR SARS-CoV-2 OR pandemic OR "infectious disease*") AND ("population ageing" OR "population aging" OR "demographic ageing" OR "demographic aging" OR "ageing population" OR "aging population" OR "demographic change" OR "demographic projection*") AND (model* OR simulat* OR "transmission dynamics"). We found five studies modelling the effect of demographic change on infectious disease transmission. However, none of these studies were fitted to the real-world trajectory of a historical pandemic, nor combined this with an official national population projection. Additionally, none of the studies considered non-pharmaceutical interventions or vaccine roll-out policy, to isolate the specific contribution of population ageing to pandemic risk in England or elsewhere.  Added value of this studyWe are the first to combine an age-stratified pandemic model, previously validated against Englands real COVID-19 trajectory, with an official long-range demographic projection and a previously set vaccine deployment policy, isolating the effect of demographic change from policy response. We show that an ageing population substantially worsens pandemic outcomes not simply due to age-adjusted risk of severe disease, but by straining age-prioritised vaccine allocation -- a mechanism not previously identified. Different migration scenarios, despite shifting the population size projected for 2047 by {+/-} five million people, had little effect, confirming age structure as the key driver. These findings have direct relevance for pandemic preparedness planning and vaccine allocation strategy in ageing societies.  Implications of all the available evidenceOur study shows that, even with no change to non-pharmaceutical interventions, the same pandemic as COVID-19 could result in a substantially greater burden in an older future population, driven less by the larger number of elderly people than by the strain ageing places on age-prioritised vaccine allocation. Pandemic preparedness plans built around current demographics instead of projected ones therefore underestimate future risk, and vaccine allocation strategies optimised for todays population structure will need revisiting as populations continue to age. Future work should test whether alternative allocation strategies can mitigate this effect, and extend this approach to household-structured models and to other ageing populations beyond England.
ER  -