Abstract:
Assessing population-level effects of vaccines and other infectious disease prevention measures is important to the field of public health. In infectious disease studies, one person\'s treatment may affect another individual\'s outcome, that is, there may be interference between units. For example, the use of bed nets to prevent malaria by one individual may have an indirect effect on other individuals living in close proximity. In some settings, individuals may form groups or clusters where interference only occurs within groups, that is, there is partial interference. Inverse probability weighted estimators have previously been developed for observational studies with partial interference. Unfortunately, these estimators are not well suited for studies with large clusters. Therefore, in this paper, the parametric g-formula is extended to allow for partial interference. G-formula estimators are proposed for overall effects, effects when treated, and effects when untreated. The proposed estimators can accommodate large clusters and do not suffer from the g-null paradox that may occur in the absence of interference. The large sample properties of the proposed estimators are derived assuming no unmeasured confounders and that the partial interference takes a particular form (referred to as \'weak stratified interference\'). Simulation studies are presented demonstrating the finite-sample performance of the proposed estimators. The Demographic and Health Survey from the Democratic Republic of the Congo is then analyzed using the proposed g-formula estimators to assess the effects of bed net use on malaria.
摘要:
评估疫苗和其他传染病预防措施的人群水平效果对公共卫生领域很重要。在传染病研究中,一个人的治疗可能会影响另一个人的结果,也就是说,单位之间可能存在干扰。例如,一个人使用蚊帐预防疟疾可能会对居住在附近的其他个人产生间接影响。在某些设置中,个人可以形成群组或集群,其中干扰只发生在群组内,也就是说,有部分干扰。以前已经开发了逆概率加权估计器,用于部分干扰的观察研究。不幸的是,这些估计器不太适合大型集群的研究。因此,在本文中,扩展了参数g公式以允许部分干扰。针对总体效果,提出了G公式估计器,治疗时的效果,以及未经治疗时的影响。拟议的估计器可以容纳大的簇,并且不会遭受在没有干扰的情况下可能发生的g-null悖论。假设没有未测量的混杂因素,并且部分干扰采用特定形式(称为“弱分层干扰”),则得出所提出的估计量的大样本属性。进行了仿真研究,证明了所提出的估计器的有限样本性能。然后使用拟议的g公式估算器对刚果民主共和国的人口和健康调查进行分析,以评估使用蚊帐对疟疾的影响。