Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
Hellenic Pasteur Institute, Athens, Greece.
Am J Epidemiol. 2018 Dec 1;187(12):2615-2622. doi: 10.1093/aje/kwy160.
Given globalization and other social phenomena, controlling the spread of infectious diseases has become an imperative public health priority. A plethora of interventions that in theory can mitigate the spread of pathogens have been proposed and applied. Evaluating the effectiveness of such interventions is costly and in many circumstances unrealistic. Most important, the community effect (i.e., the ability of the intervention to minimize the spread of the pathogen from people who received the intervention to other community members) can rarely be evaluated. Here we propose a study design that can build and evaluate evidence in support of the community effect of an intervention. The approach exploits molecular evolutionary dynamics of pathogens in order to track new infections as having arisen from either a control or an intervention group. It enables us to evaluate whether an intervention reduces the number and length of new transmission chains in comparison with a control condition, and thus lets us estimate the relative decrease in new infections in the community due to the intervention. We provide as an example one working scenario of a way the approach can be applied with a simulation study and associated power calculations.
鉴于全球化和其他社会现象，控制传染病的传播已经成为当务之急的公共卫生重点。已经提出并应用了大量理论上可以减轻病原体传播的干预措施。评估此类干预措施的有效性代价高昂，而且在许多情况下不切实际。最重要的是，社区效应（即干预措施将接受干预的人传播病原体的能力最小化到其他社区成员的能力）很少能够得到评估。在这里，我们提出了一种研究设计，可以建立和评估支持干预社区效应的证据。该方法利用病原体的分子进化动态来跟踪新感染，以确定它们是源自对照组还是干预组。它使我们能够评估干预措施与对照条件相比，是否减少了新传播链的数量和长度，从而使我们能够估计由于干预措施而导致社区中新感染的相对减少。我们提供了一个示例，说明了该方法如何与模拟研究和相关功效计算一起应用的工作方案。
