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Invited Commentary: Invited Commentary: Evaluating Vaccination Programs Using Genetic Sequence Data

机译:受邀评论:受邀评论:使用遗传序列数据评估疫苗接种计划

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摘要

Genomic data will become an increasingly important component of epidemiologic studies in coming years. The authors of the accompanying Journal article, van Ballegooijen et al. (Am J Epidemiol. 2009;170(12):1455–1463), are to be commended for attempting to use the coalescent analysis of viral sequence data to evaluate a hepatitis B vaccination program. Coalescent theory attempts to link the phylogenetic history of populations with rates of population growth and decline. In particular, under certain assumptions, a reduction in genetic diversity can be interpreted as a reduction in disease incidence. However, the authors of this commentary contend that van Ballegooijen et al.’s interpretation of changes in viral genetic diversity as a measure of hepatitis B vaccine effectiveness has major limitations. Because of the potential use of these methods in future vaccination studies, the authors discuss the utility of these methods and the data requirements needed for them to be convincing. First, data sets should be large enough to provide sufficient epidemiologic-scale resolution. Second, data need to reflect sufficiently fine-grained temporal sampling. Third, other processes that can potentially influence genetic diversity and confuse demographic inferences should be considered.
机译:未来几年,基因组数据将成为流行病学研究越来越重要的组成部分。随附的《华尔街日报》文章的作者van Ballegooijen等。 (Am J Epidemiol。2009; 170(12):1455–1463)因尝试使用病毒序列数据的合并分析来评估乙肝疫苗接种计划而受到赞扬。联合理论试图将人口的系统发育历史与人口的增长和下降速度联系起来。特别地,在某些假设下,遗传多样性的减少可以解释为疾病发病率的减少。但是,这篇评论的作者认为,范·巴拉格沃伊恩(van Ballegooijen)等人对病毒遗传多样性变化作为乙型肝炎疫苗有效性衡量标准的解释存在重大局限性。由于这些方法可能在未来的疫苗接种研究中使用,因此作者讨论了这些方法的实用性以及令人信服的数据要求。首先,数据集应足够大以提供足够的流行病学规模的分辨率。其次,数据需要反映足够细粒度的时间采样。第三,应考虑其他可能影响遗传多样性并混淆人口统计学推论的过程。

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