Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness

The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness, however, it remains subject to various potential biases. In this talk, we present a novel approach to identify and estimate vaccine effectiveness by leveraging a pair of negative control exposure and outcome variables to account for hidden bias in TND studies. We illustrate our proposed method with extensive simulation and an application to COVID-19 vaccine effectiveness using data from the University of Michigan Health System.
 

Speaker: Xu Shi, PhD, Assistant Professor of Biostatistics, University of Michigan

To obtain a Zoom link, please email epibiostat@ucsf.edu.