Modeling the Impacts of Clinical Influenza Testing on Influenza Vaccine Effectiveness Estimates

Leora R. Feldstein, Jill M. Ferdinands, Wesley H. Self, Adrienne G. Randolph, Michael Aboodi, Adrienne H. Baughman, Samuel M. Brown, Matthew C. Exline, D. Clark Files, Kevin Gibbs, Adit A. Ginde, Michelle N. Gong, Carlos G. Grijalva, Natasha Halasa, Akram Khan, Christopher J. Lindsell, Margaret Newhams, Ithan D. Peltan, Matthew E. Prekker, Todd W. RiceNathan I. Shapiro, Jay Steingrub, H. Keipp Talbot, M. Elizabeth Halloran, Manish Patel

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background: Test-negative design studies for evaluating influenza vaccine effectiveness (VE) enroll patients with acute respiratory infection. Enrollment typically occurs before influenza status is determined, resulting in over-enrollment of influenza-negative patients. With availability of rapid and accurate molecular clinical testing, influenza status could be ascertained before enrollment, thus improving study efficiency. We estimate potential biases in VE when using clinical testing. Methods: We simulate data assuming 60% vaccinated, 25% of those vaccinated are influenza positive, and VE of 50%. We show the effect on VE in 5 scenarios. Results: Vaccine effectiveness is affected only when clinical testing preferentially targets patients based on both vaccination and influenza status. Vaccine effectiveness is overestimated by 10% if nontesting occurs in 39% of vaccinated influenza-positive patients and 24% of others. VE is also overestimated by 10% if nontesting occurs in 8% of unvaccinated influenza-positive patients and 27% of others. Vaccine effectiveness is underestimated by 10% if nontesting occurs in 32% of unvaccinated influenza-negative patients and 18% of others. Conclusions: Although differential clinical testing by vaccine receipt and influenza positivity may produce errors in estimated VE, bias in testing would have to be substantial and overall proportion of patients tested would have to be small to result in a meaningful difference in VE.

Original languageEnglish (US)
Pages (from-to)2035-2042
Number of pages8
JournalJournal of Infectious Diseases
Volume224
Issue number12
DOIs
StatePublished - Dec 15 2021

Keywords

  • bias
  • clinical testing
  • influenza
  • vaccine effectiveness

ASJC Scopus subject areas

  • Immunology and Allergy
  • Infectious Diseases

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