扩展EpiEstim以实时估计病原体变体的传播优势:以严重急性呼吸系统综合征冠状病毒2型为例研究。

IF 3 3区 医学 Q2 INFECTIOUS DISEASES
Sangeeta Bhatia , Jack Wardle , Rebecca K. Nash , Pierre Nouvellet , Anne Cori
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引用次数: 1

摘要

SARS-CoV-2的演变表明,新出现的变异可能会阻碍全球新冠肺炎的应对。快速评估新变种威胁的能力对于及时优化控制策略至关重要。我们提出了一种新的方法来估计新变体与参考变体相比的有效传播优势,该参考变体结合了多个位置和一段时间的信息。通过一项旨在模拟实时流行病背景的广泛模拟研究,我们表明我们的方法在一系列场景中表现良好,并为其最佳使用和结果解释提供了指导。我们还提供了我们方法的开源软件实现。我们工具的计算速度使用户能够快速探索估计传输优势的空间和时间变化。根据英国和法国的数据,我们估计严重急性呼吸系统综合征冠状病毒2型阿尔法变种的传播力分别是野生型的1.46倍(95%可信区间1.44-1.47)和1.29倍(95%CrI 1.29-1.30)。我们进一步估计,德尔塔的传播力是阿尔法的1.77倍(95%CrI 1.69-1.85)(英格兰数据)。我们的方法可以作为实时量化新出现或共同传播的传染性病原体变种的威胁的重要第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending EpiEstim to estimate the transmission advantage of pathogen variants in real-time: SARS-CoV-2 as a case-study

The evolution of SARS-CoV-2 has demonstrated that emerging variants can set back the global COVID-19 response. The ability to rapidly assess the threat of new variants is critical for timely optimisation of control strategies.

We present a novel method to estimate the effective transmission advantage of a new variant compared to a reference variant combining information across multiple locations and over time. Through an extensive simulation study designed to mimic real-time epidemic contexts, we show that our method performs well across a range of scenarios and provide guidance on its optimal use and interpretation of results. We also provide an open-source software implementation of our method. The computational speed of our tool enables users to rapidly explore spatial and temporal variations in the estimated transmission advantage.

We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44–1.47) and 1.29 (95% CrI 1.29–1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Delta is 1.77 (95% CrI 1.69–1.85) times more transmissible than Alpha (England data).

Our approach can be used as an important first step towards quantifying the threat of emerging or co-circulating variants of infectious pathogens in real-time.

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来源期刊
Epidemics
Epidemics INFECTIOUS DISEASES-
CiteScore
6.00
自引率
7.90%
发文量
92
审稿时长
140 days
期刊介绍: Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.
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