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解析中东呼吸综合征冠状病毒(MERS-CoV)传播的驱动因素。

Unraveling the drivers of MERS-CoV transmission.

作者信息

Cauchemez Simon, Nouvellet Pierre, Cori Anne, Jombart Thibaut, Garske Tini, Clapham Hannah, Moore Sean, Mills Harriet Linden, Salje Henrik, Collins Caitlin, Rodriquez-Barraquer Isabel, Riley Steven, Truelove Shaun, Algarni Homoud, Alhakeem Rafat, AlHarbi Khalid, Turkistani Abdulhafiz, Aguas Ricardo J, Cummings Derek A T, Van Kerkhove Maria D, Donnelly Christl A, Lessler Justin, Fraser Christophe, Al-Barrak Ali, Ferguson Neil M

机构信息

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 75015 Paris, France; Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, 75015 Paris, France; Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France;

Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, Faculty of Medicine, London W2 1PG, United Kingdom;

出版信息

Proc Natl Acad Sci U S A. 2016 Aug 9;113(32):9081-6. doi: 10.1073/pnas.1519235113. Epub 2016 Jul 25.

Abstract

With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.

摘要

中东呼吸综合征冠状病毒(MERS-CoV)已造成1700多例实验室确诊感染病例,依然严重威胁着公众健康。然而,由于缺乏关于该病毒在动物宿主间及人际间传播方式的详细数据,MERS-CoV疫情的驱动因素仍未得到充分描述。在此,我们建立了一个统计框架,以全面分析2013年1月至2014年7月间在沙特阿拉伯王国(KSA)检测到的681例MERS-CoV病例的传播模式。我们评估了来自动物宿主的感染、不同程度的人际接触以及传播过程中的异质性对沙特阿拉伯MERS-CoV疫情积累的影响。我们估计,12%[95%可信区间(CI):9%,15%]的病例是来自动物宿主的感染,其余病例则是通过人际传播在聚集性疫情中感染的(60%;CI:57%,63%),在地区内传播(23%;CI:20%,27%),或在地区间传播(5%;CI:2%,8%)。聚集性疫情开始时的再生数平均为0.45(CI:0.33,0.58),但标准差较大(0.53;CI:0.35,0.78)。在12%(CI:6%,18%)的聚集性疫情中再生数大于1,但在平均出现10例病例后,再生数下降至初始值的约二分之一(47% CI:34%,63%)。鉴于医疗系统中仍有大规模疫情爆发的持续风险,人类持续接触来自动物宿主的MERS-CoV是一个主要问题。我们提出的方法能够在病例之间的关联数据仍然有限且不确定的情况下,对传染病传播进行研究。

相似文献

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Unraveling the drivers of MERS-CoV transmission.解析中东呼吸综合征冠状病毒(MERS-CoV)传播的驱动因素。
Proc Natl Acad Sci U S A. 2016 Aug 9;113(32):9081-6. doi: 10.1073/pnas.1519235113. Epub 2016 Jul 25.
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