Understanding the population-level effects of vaccines has important public health policy implications. Inferring vaccine effects from an observational study is challenging because participants are not randomized to vaccine (i.e., treatment). Observational studies of infectious diseases present the additional challenge that vaccinating one participant may affect another participant’s outcome, that is, there may be interference. In this paper recent approaches to defining vaccine effects in the presence of interference are considered, and new causal estimands designed specifically for use with observational studies are proposed. Previously defined estimands target counterfactual scenarios in which individuals independently choose to be vaccinated with equal probability. However, in settings where there is interference between individuals within clusters, it may be unlikely that treatment selection is independent between individuals in the same cluster. The proposed causal estimands instead describe counterfactual scenarios which allow for within-cluster dependence in the individual treatment selections. These estimands may be more relevant for policy-makers or public health officials who desire to quantify the effect of increasing the proportion of vaccinated individuals in a population. Inverse probability-weighted estimators for these estimands are proposed. The large-sample properties of the estimators are derived, and a simulation study demonstrating the finite-sample performance of the estimators is presented. The proposed methods are illustrated by analyzing data from a study of cholera vaccination in over 100,000 individuals in Bangladesh.

中文翻译：

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聚类干扰观察研究的因果推论，并应用于霍乱疫苗研究

了解疫苗对人口的影响具有重要的公共卫生政策意义。从观察性研究中推断疫苗的效果具有挑战性，因为参与者没有随机分配疫苗（即治疗）。传染病的观察性研究提出了另外一个挑战，即给一个参与者接种疫苗可能会影响另一参与者的结局，即可能存在干扰。在本文中，考虑了在存在干扰的情况下定义疫苗效果的最新方法，并提出了专门设计用于观察性研究的新因果估计。先前定义的估计以反事实场景为目标，在这种情况下，个人独立选择以相等概率进行疫苗接种。然而，在集群中个体之间存在干扰的环境中，相同集群中个体之间的治疗选择可能不太可能独立。拟议的因果估计改为描述了反事实情况，这些情况允许在单个治疗选择中进行群内依赖。这些估计对于希望量化增加人口中接种疫苗个体比例的影响的决策者或公共卫生官员而言可能更为相关。提出了针对这些估计的逆概率加权估计器。推导了估计量的大样本性质，并进行了仿真研究，证明了估计量的有限样本性能。通过分析来自100多个霍乱疫苗接种研究的数据来说明所建议的方法，