title: Assessment of Virus Interference in a Test-negative Study of Influenza Vaccine Effectiveness.
abstract: The observational test-negative study design is used to estimate vaccine effectiveness against influenza virus infection. An important assumption of the test-negative design is that vaccination does not affect the risk of infection with another virus. If such virus interference occurred, detection of other respiratory viruses would be more common among influenza vaccine recipients and vaccine effectiveness estimates could differ. We evaluated the potential for virus interference using data from the Influenza Incidence Surveillance Project.
  
  
  
  From 2010 to 2013, outpatients presenting to clinics in 13 US jurisdictions with acute respiratory infections were tested for influenza and other respiratory viruses. We investigated whether virus interference might affect vaccine effectiveness estimates by first evaluating the sensitivity of estimates using alternative control groups that include or exclude patients with other respiratory virus detections by age group and early/middle/late stage of influenza seasons. Second, we evaluated the association between influenza vaccination receipt and other respiratory virus detection among influenza test-negative patients.
  
  
  
  Influenza was detected in 3,743/10,650 patients (35%), and overall vaccine effectiveness was 47% (95% CI: 42%, 52%). Estimates using each control group were consistent overall or when stratified by age groups, and there were no differences among early, middle, or late phase during influenza season. We found no associations between detection of other respiratory viruses and receipt of influenza vaccination.
  
  
  
  In this 3-year test-negative design study in an outpatient setting in the United States, we found no evidence of virus interference or impact on influenza vaccine effectiveness estimation.
authors.affiliation: From the aWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; and bInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA.
authors.forename: Shuo
authors.initials: S
authors.lastname: Feng
authors.forename: Ashley L
authors.initials: AL
authors.lastname: Fowlkes
authors.forename: Andrea
authors.initials: A
authors.lastname: Steffens
authors.forename: Lyn
authors.initials: L
authors.lastname: Finelli
authors.forename: Benjamin J
authors.initials: BJ
authors.lastname: Cowling
mesh_terms: D000328:Adult; D002648:Child; D015331:Cohort Studies; D004196:Disease Outbreaks; D005188:False Negative Reactions; D005260:Female; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology; D053122:Influenza A Virus, H3N2 Subtype / Q000276:immunology; D009981:Influenza B virus / Q000276:immunology; D007252:Influenza Vaccines / Q000008:administration & dosage / Q000276:immunology*; D007251:Influenza, Human / Q000453:epidemiology* / Q000517:prevention & control / Q000821:virology*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012141:Respiratory Tract Infections / Q000453:epidemiology / Q000821:virology*; D012189:Retrospective Studies; D018570:Risk Assessment; D018571:Sentinel Surveillance; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology; D014611:Vaccination / Q000706:statistics & numerical data
chemical_list: D007252:Influenza Vaccines