Excess Influenza Hospital Admissions and Costs Due to the 2009 H1N1 Pandemic in England

Health Econ. 2019 Feb;28(2):175-188. doi: 10.1002/hec.3834. Epub 2018 Oct 18.


Influenza pandemics considerably burden affected health systems due to surges in inpatient admissions and associated costs. Previous studies underestimate or overestimate 2009/2010 influenza A/H1N1 pandemic hospital admissions and costs. We robustly estimate overall and age-specific weekly H1N1 admissions and costs between June 2009 and March 2011 across 170 English hospitals. We calculate H1N1 admissions and costs as the difference between our administrative data of all influenza-like-illness patients (seasonal and pandemic alike) and a counterfactual of expected weekly seasonal influenza admissions and costs established using time-series models on prepandemic (2004-2008) data. We find two waves of H1N1 admissions: one pandemic wave (June 2009-March 2010) with 10,348 admissions costing £20.5 million and one postpandemic wave (November 2010-March 2011) with 11,775 admissions costing £24.8 million. Patients aged 0-4 years old have the highest H1N1 admission rate, and 25- to 44- and 65+-year-olds have the highest costs. Our estimates are up to 4.3 times higher than previous reports, suggesting that the pandemic's burden on hospitals was formerly underassessed. Our findings can help hospitals manage unexpected surges in admissions and resource use due to pandemics.

Keywords: H1N1 pandemic; SARIMA; cost; hospital admissions; time series.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Cost of Illness
  • England / epidemiology
  • Female
  • Health Care Costs / statistics & numerical data*
  • Hospitalization / economics
  • Hospitalization / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • Influenza A Virus, H1N1 Subtype*
  • Influenza, Human / economics
  • Influenza, Human / epidemiology*
  • Male
  • Middle Aged
  • Models, Econometric
  • Pandemics / economics
  • Pandemics / statistics & numerical data*
  • Young Adult