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Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia

机译：东南亚SARS-COV-2的分子系统发育和时空扩散

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Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10 ?3 (1.292 × 10 ?3 to 1.613 × 10 ?3 ) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.
机译：背景：2019（Covid-19）持续的冠状病毒疾病（Covid-19）大流行为东南亚的公共卫生提出了前所未有的挑战，这是一个有限资源的热带地区。本研究旨在调查该地区严重急性呼吸综合征冠状病毒2（SARS-COV-2）的进化动力学和时空模式。材料和方法：共有1491个完整的SARS-COV-2基因组序列，来自10个东南亚国家的10个东南亚国家，从2020年11月17日分享禽流感数据（GISAID）数据库的全球倡议下载。使用最大可能性评估进化关系（ml）和时间级贝叶斯系统发育分析，并使用主成分分析（PCA）测试系统发育聚类。使用贝叶斯随机搜索变量选择（BSSVS）模型推断出东南亚SARS-COV-2的空间模式。使用贝叶斯天空格模型推断出有效的人口大小（NE）轨迹。结果：基于最大落后钢板可信度（MCC）树，识别了四个主要的片状（包括一个潜在的地方）。 PCA产生类似的聚类;前三名PC在样品中解释了总基因组变异的46.9％。最近常见的祖先（TMRCA）和SARS-COV-2在东南亚的进化率的时间估计是2019年11月28日（2019年9月7日至1月4日，2020年）和1.446×10？3 （1.292×10？3至1.613×10？3）每年替换每年。新加坡和泰国是两个最可能的根位置，分别为0.549和0.413的后验概率。新加坡，马来西亚和印度尼西亚有高支撑传输链路（贝叶斯因子超过1,000）;马来西亚涉及该地区内部推断传输链路的最高数量（7）。在东南亚大流行的早期阶段推断出两次加速的病毒人口扩张，其次是临时挫折。结论：具有可用的基因组数据，我们说明了在东南亚循环的SARS-COV-2的局部摄影和文学学报。持续的基因组监测和增强的战略合作应被列为遏制大流行的优先事项，特别是对于由发展中国家主导的地区社区为主。

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