Assessment of the variability in influenza A(H1N1) vaccine effectiveness estimates dependent on outcome and methodological approach

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Estimation of Influenza vaccine effectiveness (VE) varies with study design, clinical outcome 10 considered and statistical methodology used. By estimating VE using differing outcomes and 11 statistical methods on the same cohort of individuals the variability in the estimates produced can 12 be better understood. The Pandemic Influenza Primary Care Reporting (PIPeR) cohort of approximately 193,000 individuals 14 was used to estimate pandemic VE in Scotland during season 2009-10. VE results for three 15 outcomes; influenza related consultations, virological confirmed influenza and death were 16 considered. Use of individualised records allowed all models to be adjusted for age, sex, 17 deprivation, risk status relating to chronic illnesses, seasonal vaccination status and a marker of the 18 individual’s propensity to consult. For the consultation and death outcomes, VE was calculated by 19 comparing consultation rates in the unvaccinated and vaccinated groups, adjusted for the listed 20 factors, using both Cox and Poisson regression models. For the consultation outcome, the 21 unvaccinated group was split into individuals before vaccination and those never vaccinated to allow 22 for potential differences in the health seeking behaviour of these groups. For the virology outcome 23 estimates were calculated using a generalised additive logistic regression model. All models were 24 adjusted for time. Vaccine effect was demonstrated for the influenza-like illness consultation outcome using the Cox 26 model (VE=49% 95% CI (19%, 67%)) with lower estimates from the model splitting the before and 27 never vaccinated groups (VE=34.2% with 95% CI (-0.5%, 58.9%)). Vaccine effect was also illustrated 28 for overall mortality (VE=40% (95% CI 18%, 56%)) and a virological confirmed subset of symptomatic 29 individuals (VE=60% (95% CI -38%, 89%)).
Original languageEnglish
Article numbere28743
Number of pages12
JournalPLoS One
Issue number12
Early online date22 Dec 2011
Publication statusPublished - 2011


  • influenza
  • variability
  • mathematical analysis


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