A Probability Model for Comparing Estimates of Influenza Vaccine Effectiveness from Case-Control Studies

• Activity Number: 702
• Type: Contributed
• Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Michael Haber* and Qian An and Meng Shi
• Companies: Emory University and Emory University and Emory University
• Keywords: Influenza ; Vaccine Effectiveness ; Case-control studies ; Test-negative design ; Bias ; Infectious disease models

Abstract

As influenza vaccination is now widely recommended, randomized clinical trials for estimating influenza vaccine effectiveness (IVE) are no longer ethical in many populations and observational studies based on patients seeking medical care for acute respiratory illnesses (ARI) remain the only option. We developed a probability model for comparing the bias of IVE estimates from two popular case-control designs. In both study designs, ARI patients seeking medical care who test positive for influenza infection are considered cases. In the test-negative design, ARI patients seeking medical care who test negative for influenza infection serve as controls. In the traditional case-control design, controls are randomly selected from the population. We considered two possible outcomes against which the vaccine is supposed to protect: symptomatic influenza (SI) and medically-attended influenza (MAI). Our theoretical and numerical results suggest that estimates from the test-negative design usually have smaller bias when the outcome of interest is SI, while estimates from the traditional case-control design usually have smaller bias when the outcome of interest is MAI.