Uses of pathogen detection data to estimate vaccine direct effects in case-control studies.

Abstract

The fact that many pathogens can be carried or shed without causing symptoms complicates the interpretation of microbiological data when diagnosing certain infectious disease syndromes. Diagnostic criteria that attribute symptoms to a pathogen which is detectable, whether it is or is not the aetiological agent of disease, may lead to outcome misclassification in epidemiological studies. Case-control studies are commonly undertaken to estimate vaccine effectiveness (VE) and present an opportunity to compare pathogen detection among individuals with and without clinically relevant symptoms. Considering this study context, we present a mathematical framework yielding simple estimators for the direct effects of vaccination on various aspects of host susceptibility. These include protection against acquisition of the pathogen of interest and protection against progression of this pathogen to disease following acquisition. We assess the impact of test sensitivity on these estimators and extend our framework to identify a 'vaccine probe' estimator for pathogen-specific aetiological fractions. We also derive biases affecting VE estimates under the test-negative design, a special case enrolling only symptomatic persons. Our results provide strategies for estimating pathogen-specific VE in the absence of a diagnostic gold standard. These approaches can inform the design and analysis of studies addressing numerous pathogens and vaccines.