Bounds for the Causal Infectiousness Effect in Vaccine Trials

• Activity Number: 657
• Type: Contributed
• Date/Time: Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Yasutaka Chiba*+
• Keywords: Causal inference ; Partial interference ; Potential outcome ; Principal stratification

Abstract

The vaccine status of one person may affect whether another person becomes infected. This phenomenon is sometimes referred to as interference, and it makes it difficult to estimate the causal effect of a vaccine on infection, i.e., the causal infectiousness effect (CIE). We consider households of two individuals in which one of the two individuals (individual 1) is randomized to receive a vaccine or control, and the other (individual 2) receives nothing. In this setting, using the counterfactual notation and principal stratification framework, the CIE is defined as the causal effect for individual 2 in the principal stratum of households for whom individual 1 would have been infected irrespective of whether individual 1 was vaccinated. Here, we present the CIE bounds under an assumption of partial interference that the vaccine status of persons in one household in the study does not affect the outcomes of those in other study households. First, we present the large sample bounds with no assumption. Next, we improve the large sample bounds by strengthening one of two plausible assumptions given by VanderWeele and Tchetgen Tchetgen (Epidemiology 2011; 22: 686-693).