Determining whether vaccine efficacy wanes is important for individual and public decision making. Yet, quantification of waning is a subtle task. The classical approaches cannot be interpreted as measures of declining efficacy unless we impose unreasonable assumptions. Recently, formal causal estimands designed to quantify vaccine waning have been proposed. These estimands can be bounded under weaker assumptions, but the bounds are often too wide to make claims about the presence of waning. We propose a different approach: a formal test to assess whether a treatment effect is constant over time at the individual level. This test provides a considerable power gain over existing approaches and is valid under interpretable assumptions in vaccine trials. We illustrate the increase in power through real and simulated examples, using three different approaches to compute the test statistics. Two of these approaches are based solely on summary data, accessible from existing clinical trials. Beyond our test, we also give new results that bound the waning effect. We use our methods to reanalyze data from a randomized controlled trial of the BNT162b2 COVID-19 vaccine. While prior analysis did not establish waning, our test rejects the null hypothesis of no waning.

翻译：确定疫苗效力是否随时间衰减对个体和公共卫生决策至关重要。然而，量化衰减是一项精细的工作。除非施加不合理的假设，否则传统方法无法被解释为效力下降的衡量指标。近期，研究者提出了旨在量化疫苗衰减的形式化因果估计量。这些估计量在较弱假设下可被界定，但边界往往过宽，难以判断衰减是否存在。我们提出了一种不同方法：一个正式检验，用于评估个体层面的治疗效果是否随时间保持恒定。该检验相比现有方法具有显著的统计功效提升，并在疫苗临床试验的可解释假设下有效。我们通过真实与模拟案例，采用三种不同方式计算检验统计量，展示了功效的提升。其中两种方式仅基于现有临床试验可获取的汇总数据。除检验方法外，我们还给出了界定衰减效应的新结果。我们应用所提方法重新分析了BNT162b2新冠疫苗随机对照试验数据。尽管既往分析未能证实衰减存在，但我们的检验拒绝了无衰减的原假设。