Statistical Challenges in Tracking the Evolution of SARS-CoV-2.

IF 3.9 1区 数学 Q1 STATISTICS & PROBABILITY
Statistical Science Pub Date : 2022-05-01 Epub Date: 2022-05-16 DOI:10.1214/22-sts853
Lorenzo Cappello, Jaehee Kim, Sifan Liu, Julia A Palacios
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引用次数: 0

Abstract

Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the virus, its evolutionary rate, the timing of introductions, the patterns of transmission, and the rise of novel variants that have spread through populations. Despite enormous global efforts of governments, laboratories, and researchers to collect and sequence molecular data, many challenges remain in analyzing and interpreting the data collected. Here, we describe the models and methods currently used to monitor the spread of SARS-CoV-2, discuss long-standing and new statistical challenges, and propose a method for tracking the rise of novel variants during the epidemic.

Abstract Image

追踪 SARS-CoV-2 演变的统计挑战。
对 SARS-CoV-2 的基因组监测有助于追踪病毒在大流行期间的传播和演变情况。从感染者身上分离出的 SARS-CoV-2 分子序列的可用性,加上系统动力学方法,使人们对病毒的起源、进化速度、引入时间、传播模式以及在人群中传播的新型变种的出现有了更深入的了解。尽管各国政府、实验室和研究人员在收集分子数据并对其进行测序方面做出了巨大的全球努力,但在分析和解释所收集的数据方面仍存在许多挑战。在此,我们将介绍目前用于监测 SARS-CoV-2 传播的模型和方法,讨论长期存在的和新的统计挑战,并提出一种在疫情期间跟踪新型变异体增加的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Statistical Science
Statistical Science 数学-统计学与概率论
CiteScore
6.50
自引率
1.80%
发文量
40
审稿时长
>12 weeks
期刊介绍: The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.
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