Symmetric Vaccine Efficacy
By: Lucy D'Agostino McGowan, Sarah C. Lotspeich, Michael G. Hudgens
Potential Business Impact:
Measures how well vaccines work, good or bad.
Traditional measures of vaccine efficacy (VE) are inherently asymmetric, constrained above by $1$ but unbounded below. As a result, VE estimates and corresponding confidence intervals can extend far below zero, making interpretation difficult and potentially obscuring whether the apparent effect reflects true harm or simply statistical uncertainty. The proposed symmetric vaccine efficacy (SVE) is a bounded and interpretable alternative to VE that maintains desirable statistical properties while resolving these asymmetries. SVE is defined as a symmetric transformation of infection risks, with possible values within $[-1, 1]$, providing a common scale for both beneficial and harmful vaccine effects. This paper describes the relationship between SVE and traditional VE, considers inference about SVE, and illustrates the utility of the proposed measure by reanalyzing data from a randomized trial of a candidate HIV vaccine. Open-source tools for computing estimates of SVE and corresponding confidence intervals are available in R through the sve package.
Similar Papers
Nonparametric bounds for vaccine effects in randomized trials
Methodology
Finds vaccine's true protection, even if people know they got it.
Debiasing hazard-based, time-varying vaccine effects using vaccine-irrelevant infections: An observational extension of a pivotal Phase 3 COVID-19 vaccine efficacy trial
Methodology
Makes vaccine protection estimates more accurate over time.
Temporal Exposure Dependence Bias in Vaccine Efficacy Trials
Methodology
Fixes how we measure if vaccines work.