Robust evaluation of vaccine effects based on estimation of vaccine efficacy curve
Ziwei Zhao, Xiangmei Ma, Paul Milligan, Yin Bun Cheung

TL;DR
This paper introduces a new method to estimate vaccine efficacy over time, addressing biases and limitations of traditional models, and demonstrates its advantages through simulations and real trial data analysis.
Contribution
It proposes a novel approach to estimate vaccine efficacy as a function of time using the Cox model, improving robustness and comparability across trials.
Findings
The method provides unbiased estimates under waning immunity scenarios.
It improves comparability of vaccine efficacy across different trial designs.
The approach helps optimize vaccine delivery timing in seasonal disease regions.
Abstract
Background: The Cox model and its extensions assuming proportional hazards is widely used to estimate vaccine efficacy (VE). In the typical situation that VE wanes over time, the VE estimates are not only sensitive to study duration and timing of vaccine delivery in relation to disease seasonality but also biased in the presence of sample attrition. Furthermore, estimates of vaccine impact such as number of cases averted (NCA) are sensitive to background disease incidence and timing of vaccine delivery. Comparison of the estimates between trials with different features can be misleading. Methods: We propose estimation of VE as a function of time in the Cox model framework, using the area under the VE curve as a summary measure of VE, and extension of the method to estimate vaccine impact. We use simulations and re-analysis of a RTS,S/AS01 malaria vaccine trial dataset to demonstrate…
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Taxonomy
TopicsHepatitis B Virus Studies · Hepatitis C virus research · vaccines and immunoinformatics approaches
