{"title":"Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples.","authors":"Lucy D'Agostino McGowan, Shirlee Wohl, Justin Lessler","doi":"10.1093/aje/kwae378","DOIUrl":null,"url":null,"abstract":"<p><p>The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/aje/kwae378","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.
我们从病原体序列数据中进行推断的质量取决于用于推断的样本中病原体序列的数量和组成。然而,在以系统发育推断为最终目标时,如何最有效地构建和加强研究方面的指导仍然有限。我们可以尝试用分子数据回答的一个问题是,是否有些人比其他人更有可能传播病原体。在此,我们提出了一种估算方法,利用分子数据连接的传播对,通过具有不同特征的人群之间的繁殖数量比来量化差异传播,同时还提出了该估算方法的样本量计算方法。我们还对我们的方法进行了扩展,以纠正传播关联对的不完全识别、传播过程中的过度分散以及群体失衡。我们通过模拟验证了这一方法,并提供了在 R 软件包 phylosamp 中实现这一方法的工具。
期刊介绍:
The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research.
It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.