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Author Notes:

Corresponding author: Centers for Disease Control and Prevention, 1600 Clifton Road NE, MS A-20, Atlanta, GA 30333, USA. vor1@cdc.gov

We would like to thank Drs David Shay and Jerry Tokars, both CDC, for their helpful comments on the manuscript.

We are not aware of any potential conflict of interest.


Research Funding:

MJH’s research was supported by the National Institute of Allergies and Infectious Diseases of the National Institutes of Health (NIH) under Award R01AI110474, and by Intergovernmental Personnel Act (IPA) 1110376-05 from the Centers for Disease Controls and Prevention (CDC).


  • Science & Technology
  • Life Sciences & Biomedicine
  • Public, Environmental & Occupational Health
  • Influenza vaccine effectiveness
  • test-negative design
  • influenza-associated hospitalization
  • selection bias
  • computer simulation

The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings

Journal Title:

International Journal of Epidemiology


Volume 45, Number 6


, Pages 2052-2059

Type of Work:

Article | Final Publisher PDF


Background: The test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting. Methods: We derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies. Results: VE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates. Conclusions: The inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis.

Copyright information:

© The Author 2016

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/).

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