Estimating influenza vaccine effectiveness using routinely collected laboratory data
- D M Fleming1,
- N J Andrews3,
- J S Ellis4,
- A Bermingham4,
- P Sebastianpillai4,
- A J Elliot1,6,
- E Miller5,
- M Zambon2
- 1Royal College of General Practitioners Research and Surveillance Centre, Birmingham, UK
- 2Health Protection Agency Centre for Infections, London, UK
- 3Statistics division, Health Protection Agency Centre for Infections, London, UK
- 4Influenza virus reference laboratory, Health Protection Agency Centre for Infections, London, UK
- 5Immunisation division, Health Protection Agency Centre for Infections, London, UK
- 6Real-time Syndromic Surveillance Team, Health Protection Agency West Midlands, Birmingham, UK
- Correspondence to Dr Douglas M Fleming, Royal College of General Practitioners Research and Surveillance Centre, Lordswood House, 54 Lordswood Road, Harborne, Birmingham B17 9DB, UK;
Contributors The use of these data for the estimation of vaccine effectiveness was conceptualised by EM, NA, MZ and DF. The primary analysis was undertaken by NA. JE, AB and PS have been responsible for the laboratory work, working under the supervision of MZ. AE has had responsibilities in monitoring clinical incidence. All authors have contributed to the drafting of this manuscript and have approved it. No contribution has been omitted from authorship.
- Accepted 18 October 2009
- Published Online First 12 November 2009
Background Estimation of influenza vaccine effectiveness (V/E) is needed early during influenza outbreaks in order to optimise management of influenza—a need which will be even greater in a pandemic situation.
Objective Examine the potential of routinely collected virological surveillance data to generate estimates of V/E in real-time during winter seasons.
Methods Integrated clinical and virological community influenza surveillance data collected over three winters 2004/5–2006/7 were used. We calculated the odds of vaccination in persons that were influenza-virus-positive and the odds in those that were negative and provided a crude estimate of V/E. Logistic regression was used to obtain V/E estimates adjusted for confounding variables such as age.
Results Multivariable analysis suggested that adjustments to the crude V/E estimate were necessary for patient age and month of sampling. The annual adjusted V/E was 2005/6, 67% (95% CI 41% to 82%); 2006/7 55% (26% to 73%) and 2007/8 67% (41% to 82%). The adjusted V/E in persons <65 years was 70% (57% to 78%) and 65 years and over 46% (−17% to 75%). Estimates differed by small insignificant amounts when calculated separately for influenza A and B; by interval between illness onset and swab sample; by analysis for the period November to January in each year compared with February to April and according to viral load.
Conclusion We have demonstrated the potential of using routine virological and clinical surveillance data to provide estimates of V/E early in season and conclude that it is feasible to introduce this approach to V/E measurement into evaluation of national influenza vaccination programs.
Funding This study has been undertaken within the routine budgets of the collaborating participants.
Competing interests DMF has received funding to attend influenza-related meetings and has received consultancy fees from influenza vaccine manufacturers. HPA receives funding from a variety of vaccine manufacturers for work in Maria Zambon's laboratory.
Provenance and peer review Not commissioned; externally peer reviewed.