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

Estimation of Influenza vaccine effectiveness (VE) varies with study design, clinical outcome considered and statistical methodology used. By estimating VE using differing outcomes and statistical methods on the same cohort of individuals the variability in the estimates produced can be better understood. The Pandemic Influenza Primary Care Reporting (PIPeR) cohort of approximately 193,000 individuals was used to estimate pandemic VE in Scotland during season 2009-10. VE results for three outcomes; influenza related consultations, virological confirmed influenza and death were considered. Use of individualised records allowed all models to be adjusted for age, sex, deprivation, risk status relating to chronic illnesses, seasonal vaccination status and a marker of the individual's propensity to consult. For the consultation and death outcomes, VE was calculated by comparing consultation rates in the unvaccinated and vaccinated groups, adjusted for the listed factors, using both Cox and Poisson regression models. For the consultation outcome, the unvaccinated group was split into individuals before vaccination and those never vaccinated to allow for potential differences in the health seeking behaviour of these groups. For the virology outcome estimates were calculated using a generalised additive logistic regression model. All models were adjusted for time. Vaccine effect was demonstrated for the influenza-like illness consultation outcome using the Cox model (VE=49% 95% CI (19%, 67%)) with lower estimates from the model splitting the before and never vaccinated groups (VE=34.2% with 95% CI (-0.5%, 58.9%)). Vaccine effect was also illustrated for overall mortality (VE=40% (95% CI 18%, 56%)) and a virological confirmed subset of symptomatic individuals (VE=60% (95% CI -38%, 89%)).This study illustrates positive point estimates of Influenza VE across methodology and outcome for a single cohort of individuals during season 2009-10. Understanding of potential differences between approaches aids interpretation of VE results in future seasons