A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages
A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages
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系统动力学工作流程可快速了解 SARS-CoV-2 谱系的传播历史和动态
DOI：
10.1101/2020.05.05.078758
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发表时间：
2020
影响因子：
10.7
通讯作者：
P. Maes
中科院分区：
文献类型：
--
作者：
S. Dellicour;K. Durkin;S. Hong;B. Vanmechelen;Joan Martí;Mandev S. Gill;C. Meex;S. Bontems;E. André;M. Gilbert;C. Walker;N. de Maio;N. Faria;J. Hadfield;M. Hayette;V. Bours;Tony Wawina;M. Artesi;G. Baele;P. Maes
自 COVID-19 大流行开始以来，已生成数量空前数量的致病病毒 (SARS-CoV-2) 基因组序列并与科学界共享。无与伦比的可用遗传数据量为实时了解大流行期间的病毒传播提供了独特的机会，但如果使用金标准系统发育地理学方法进行分析，这也是一个令人畏惧的计算障碍。我们在这里描述并应用一个分析管道，它是快速和严格分析步骤之间的折衷方案。作为概念验证，我们重点关注比利时的流行病，该流行病是可用 SARS-CoV-2 基因组空间密度最高的流行病之一。在全球范围内，我们的分析证实了外部引入事件对于在该国建立多个传播链的重要性。在国家尺度上，我们的空间明确的系统发育地理学分析强调，国家封锁对比利时境内的谱系扩散速度和长距离扩散事件的影响相对较小。我们的管道有可能迅速应用于其他国家或地区，其主要好处是补充流行病学分析，评估干预措施或其逐步缓解的影响。
Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of the causative virus (SARS-CoV-2) have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analysed with gold-standard phylogeographic approaches. We here describe and apply an analytical pipeline that is a compromise between fast and rigorous analytical steps. As a proof of concept, we focus on the Belgium epidemic, with one of the highest spatial density of available SARS-CoV-2 genomes. At the global scale, our analyses confirm the importance of external introduction events in establishing multiple transmission chains in the country. At the country scale, our spatially-explicit phylogeographic analyses highlight that the national lockdown had a relatively low impact on both the lineage dispersal velocity and the long-distance dispersal events within Belgium. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.
影响因子：
10.7
作者：
Lemey, Philippe;Rambaut, Andrew;Suchard, Marc A.
通讯作者：
Suchard, Marc A.
影响因子：
5.3
作者：
Suchard MA;Lemey P;Baele G;Ayres DL;Drummond AJ;Rambaut A
通讯作者：
Rambaut A
DNA 序列分析。
影响因子：
2.3
作者：
Weir,BS
通讯作者：
Weir,BS