Causal Inference in the Study of Infectious Disease

Abstract

Abstract The potential outcomes framework for causal inference has proven valuable in the study of infectious diseases. Conversely, the context of infectious diseases has stimulated many methodological advances in causal inference. In this chapter, we review causal inference problems pertinent to the study of infectious diseases. These include time-varying confounding, interference, and surrogate measures of clinical outcomes. The test-negative study design and the relatively new (to epidemiology) methods of negative controls and regression discontinuity are also covered. Motivation for each topic is given along with examples of application.