Related Experiment Video
Updated: May 31, 2026

Micro-Colony Forming Unit Assay for Efficacy Evaluation of Vaccines Against Tuberculosis
Published on: July 28, 2023
Bounding the infectiousness effect in vaccine trials
Tyler J VanderWeele1, Eric J Tchetgen Tchetgen
1Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. tvanderw@hsph.harvard.edu
Abstract:
In vaccine trials, the vaccination of one person might prevent the infection of another; a distinction can be drawn between the ways such a protective effect might arise. Consider a setting with 2 persons per household in which one of the 2 is vaccinated. Vaccinating the first person may protect the second person by preventing the first from being infected and passing the infection on to the second. Alternatively, vaccinating the first person may protect the second by rendering the infection less contagious even if the first is infected. This latter mechanism is sometimes referred to as an "infectiousness effect" of the vaccine. Crude estimators for the infectiousness effect will be subject to selection bias due to stratification on a postvaccination event, namely the infection status of the first person. We use theory concerning causal inference under interference along with a principal-stratification framework to show that, although the crude estimator is biased, it is, under plausible assumptions, conservative for what one might define as a causal infectiousness effect. This applies to bias from selection due to the persons in the comparison, and also to selection due to pathogen virulence. We illustrate our results with an example from the literature.
Related Concept Videos
Vaccinations
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Smallpox
Bias in Epidemiological Studies
Confounding in Epidemiological Studies
Cross-reactivity

