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ISDS 2016 Conference Abstracts

The test-negative design for estimating influenza 
vaccination effectiveness
Benjamin J. Cowling*1 and Sheena G. Sullivan2, 3
1School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong; 2WHO Collaborating Centre for Reference and 
Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia; 3Fielding School of Public 
Health, University of California, Los Angeles, CA, USA

Objective
We aimed to describe the theoretical basis and the potential 

applications of the test-negative design for estimating influenza 
vaccination effectiveness in sentinel influenza surveillance.

Introduction
The test-negative design is a variation of the case-control study, 

in which patients are enrolled in outpatient clinics (and/or hospitals) 
based on a clinical case definition such as influenza-like illness (ILI). 
Patients are then tested for influenza virus, and VE is estimated from 
the odds ratio comparing the odds of vaccination among patients 
testing positive for influenza versus those testing negative, adjusting 
for potential confounding factors. The design leverages existing 
disease surveillance networks and as a result, studies using it are 
increasingly being reported.

Methods
We sought to examine the theoretical basis for this design using 

causal analysis including directed acyclic graphs. We reviewed 
studies that used this design and examined the study populations and 
settings, the methodologic choices including analytic approaches, and 
the estimates of influenza VE provided. We conducted simulation 
studies to examine specific potential biases.

Results
We show how studies using this design can avoid or minimize 

bias, and where bias may be introduced with particular study design 
variations. A purported advantage of the test-negative design 
is to minimise selection bias by health-care seeking behaviour 
and we demonstrate why residual bias may occur. Another 
purported advantage of the test-negative design is minimization of 
misclassification of the exposure; however we show how this source 
of bias may persist and how exposure misclassification may be 
a greater cause for concern not dealt with by the study design. In 
our review, we found great variation in estimates, but consistency 
between interim and final VE estimates from the same locations, 
and consistency between VE estimates from inpatient and outpatient 
studies in the same locations, age groups and years. One outstanding 
issue is the potential bias due to non-collapsibility.

Conclusions
Our work provides a starting point for further consideration of the 

validity of the test-negative design, which is an efficient approach 
for routine monitoring of influenza VE that can be implemented in 
existing surveillance systems without substantial additional resources. 
Harmonization of analytic approaches may improve the potential for 
pooling VE estimates.

Keywords
influenza; VE; sentinel

*Benjamin J. Cowling
E-mail: bcowling@hku.hk

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e25, 2017