Department of Statistics, University of Illinois Urbana-Champaign, Champaign, USA.
Department of Public Health Sciences, Biological Sciences Division, The University of Chicago, Chicago, USA.
J Math Biol. 2022 Sep 20;85(4):37. doi: 10.1007/s00285-022-01801-8.
Randomized trials of infectious disease interventions, such as vaccines, often focus on groups of connected or potentially interacting individuals. When the pathogen of interest is transmissible between study subjects, interference may occur: individual infection outcomes may depend on treatments received by others. Epidemiologists have defined the primary parameter of interest-called the "susceptibility effect"-as a contrast in infection risk under treatment versus no treatment, while holding exposure to infectiousness constant. A related quantity-the "direct effect"-is defined as an unconditional contrast between the infection risk under treatment versus no treatment. The purpose of this paper is to show that under a widely recommended randomization design, the direct effect may fail to recover the sign of the true susceptibility effect of the intervention in a randomized trial when outcomes are contagious. The analytical approach uses structural features of infectious disease transmission to define the susceptibility effect. A new probabilistic coupling argument reveals stochastic dominance relations between potential infection outcomes under different treatment allocations. The results suggest that estimating the direct effect under randomization may provide misleading conclusions about the effect of an intervention-such as a vaccine-when outcomes are contagious. Investigators who estimate the direct effect may wrongly conclude an intervention that protects treated individuals from infection is harmful, or that a harmful treatment is beneficial.
随机对照传染病干预试验,如疫苗,通常集中在具有联系或潜在相互作用的个体群体上。当研究对象之间存在传染性病原体时,可能会发生干扰:个体感染结果可能取决于其他人接受的治疗。流行病学家将感兴趣的病原体定义为“易感性效应”,这是一种治疗与不治疗条件下的感染风险对比,同时保持对传染性的暴露不变。相关的数量是“直接效应”,定义为治疗与不治疗条件下的感染风险的无条件对比。本文的目的是表明,在一种广泛推荐的随机设计下,当结果具有传染性时,直接效应可能无法恢复干预随机试验中干预的真实易感性效应的符号。分析方法利用传染病传播的结构特征来定义易感性效应。新的概率耦合论证揭示了不同治疗分配下潜在感染结果之间的随机优势关系。结果表明,当结果具有传染性时,估计直接效应可能会对干预措施(如疫苗)的效果产生误导性结论。估计直接效应的研究人员可能会错误地得出结论,即保护治疗个体免受感染的干预措施是有害的,或者有害的治疗是有益的。