Institut PASTEUR Algérie, Algiers, Algeria.
Faculty of Sciences, University of M'sila, M'sila, Algeria.
J Med Virol. 2021 Jan;93(1):564-568. doi: 10.1002/jmv.26333. Epub 2020 Jul 27.
We present a phylodynamic and phylogeographic analysis of this new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in this report. A tree of maximum credibility was constructed using the 72 entire genome sequences of this virus, from the three countries (China, Italy, and Spain) available as of 26 March 2020 on the GISAID reference frame. To schematize the current SARS-CoV-2 migration scenario between and within the three countries chosen, using the multitype bearth-death model implemented in BEAST2. Bayesian phylogeographic reconstruction shows that SARS-CoV-2 has a rate of evolution of 2.11 × 10 per sites per year (95% highest posterior density: 1.56 × 10 to 3.89 × 10 ), and a geographic origin in Shanghai, where time until the most recent common ancestor (tMRCA) emerged, according to the analysis of the molecular clock, around 13 November 2019. While for Italy and Spain, there are two tMRCA for each country, which agree with the assumption of several introductions for these countries. That explains also this very short period of subepidermal circulation before the recent events. A total of 8 (median) migration events occurred during this short period, the largest proportion of which (6 events [75%]) occurred from Shanghai (China) to Spain and from Italy to Spain. Such events are marked by speeds of migration that are comparatively lower as compared with that from Shanghai to Italy. Shanghai's R and Italy's are closer to each other, though Spain's is slightly higher. All these results allow us to conclude the need for an automatic system of mixed, molecular and classical epidemiological surveillance, which could play a role in this global surveillance of public health and decision-making.
我们在本报告中介绍了这种新的严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)病毒的系统发育和系统地理分析。使用截至 2020 年 3 月 26 日在 GISAID 参考框架上提供的来自三个国家(中国、意大利和西班牙)的 72 个该病毒的全基因组序列,构建了一棵最大可信度树。为了用 BEAST2 中实现的多型生灭模型来示意选择的三个国家之间和内部当前 SARS-CoV-2 迁移情景,使用贝叶斯系统地理重建表明,SARS-CoV-2 的进化率为每年每个位点 2.11×10(95%最高后验密度:1.56×10 至 3.89×10),其地理起源于上海,根据分子钟分析,最接近的共同祖先(tMRCA)时间大约在 2019 年 11 月 13 日。而对于意大利和西班牙,每个国家都有两个 tMRCA,这与对这些国家的多次引入假设相符。这也解释了最近事件之前这段非常短的亚表皮循环期。在这段短时间内总共发生了 8 次(中位数)迁移事件,其中最大比例(6 次[75%])发生在中国上海到西班牙和意大利到西班牙。这些事件的迁移速度相对较低,与从上海到意大利的迁移速度相比。上海的 R 和意大利的 R 彼此更接近,尽管西班牙的 R 略高。所有这些结果都使我们得出结论,需要建立一个自动的混合、分子和经典流行病学监测系统,该系统可以在全球公共卫生监测和决策中发挥作用。