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Author Notes:

Correspondence: Kylie E. C. Ainslie, k.ainslie@imperial.ac.uk, +44 (0)20 7594 1379

Disclosures: The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.


Research Funding:

This research was supported by the Wellcome Trust (UK) Investigator Award 200861/Z/16/Z, the National Institute of Allergies and Infectious Diseases of the National Institutes of Health (US) under Award R01AI110474, and by IPA 1110376–05 with the Centers for Disease Controls and Prevention (US).


  • Science & Technology
  • Life Sciences & Biomedicine
  • Immunology
  • Influenza
  • vaccination
  • effectiveness
  • challenges
  • test-negative
  • case-control
  • cohort
  • bias
  • waning
  • confounding
  • Test negative design
  • Community dwelling adults
  • Oral cholera vaccine
  • Rotavirus vaccine
  • Virus infections
  • Selection bias
  • United States
  • Older adults
  • A-Vaccine
  • Efficacy

Challenges in estimating influenza vaccine effectiveness


Journal Title:

Expert Review of Vaccines


Volume 18, Number 6


, Pages 615-628

Type of Work:

Article | Post-print: After Peer Review


Introduction: Influenza vaccination is regarded as the most effective way to prevent influenza infection. Due to the rapid genetic changes that influenza viruses undergo, seasonal influenza vaccines must be reformulated and re-administered annually necessitating the evaluation of influenza vaccine effectiveness (VE) each year. The estimation of influenza VE presents numerous challenges. Areas Covered: This review aims to identify, discuss, and, where possible, offer suggestions for dealing with the following challenges in estimating influenza VE: different outcomes of interest against which VE is estimated, study designs used to assess VE, sources of bias and confounding, repeat vaccination, waning immunity, population level effects of vaccination, and VE in at-risk populations. Expert Opinion: The estimation of influenza VE has improved with surveillance networks, better understanding of sources of bias and confounding, and the implementation of advanced statistical methods. Future research should focus on better estimates of the indirect effects of vaccination, the biological effects of vaccination, and how vaccines interact with the immune system. Specifically, little is known about how influenza vaccination impacts an individual’s infectiousness, how vaccines wane over time, and the impact of repeated vaccination.

Copyright information:

© 2019 Informa UK Limited, trading as Taylor & Francis Group

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