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中东呼吸综合征冠状病毒(MERS-CoV)在中东的流行评估及采用新型最大似然分析方法评估国际传播风险。

Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.

机构信息

Inserm, U707, Paris, France.

出版信息

Euro Surveill. 2014 Jun 12;19(23):20824. doi: 10.2807/1560-7917.es2014.19.23.20824.

DOI:10.2807/1560-7917.es2014.19.23.20824
PMID:24957746
Abstract

The emergence of the novel Middle East (ME) respiratory syndrome coronavirus (MERS-CoV) has raised global public health concerns regarding the current situation and its future evolution. Here we propose an integrative maximum likelihood analysis of both cluster data in the ME and importations in a set of European countries to assess the transmission scenario and incidence of sporadic infections. Our approach is based on a spatial-transmission model integrating mobility data worldwide and allows for variations in the zoonotic/environmental transmission and under-ascertainment. Maximum likelihood estimates for the ME, considering outbreak data up to 31 August 2013, indicate the occurrence of a subcritical epidemic with a reproductive number R of 0.50 (95% confidence interval (CI): 0.30-0.77) associated with a daily rate of sporadic introductions psp of 0.28 (95% CI: 0.12-0.85). Infections in the ME appear to be mainly dominated by zoonotic/environmental transmissions, with possible under-ascertainment (ratio of estimated to observed (0.116) sporadic cases equal to 2.41, 95% CI: 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from ME countries indicate areas at high risk of importation. While dismissing an immediate threat for global health security, this analysis provides a baseline scenario for future reference and updates, suggests reinforced surveillance to limit under-ascertainment, and calls for alertness in high importation risk areas worldwide.

摘要

新型中东呼吸综合征冠状病毒(MERS-CoV)的出现引起了全球公共卫生部门对当前形势及其未来演变的关注。在这里,我们提出了一种综合最大似然分析方法,该方法同时考虑了中东地区的聚集性数据和一组欧洲国家的输入性病例,以评估传播情景和散发感染的发生率。我们的方法基于一个整合了全球人口流动数据的空间传播模型,该模型可以考虑人畜共患病/环境传播和漏报的变化。对中东地区的最大似然估计,考虑到截至 2013 年 8 月 31 日的暴发数据,表明存在一个亚临界流行,其繁殖数 R 为 0.50(95%置信区间:0.30-0.77),与每日散发感染率 psp 为 0.28(95%置信区间:0.12-0.85)相关。中东地区的感染似乎主要由人畜共患病/环境传播主导,可能存在漏报(估计病例与观察病例之比为 0.116,为 2.41,95%置信区间:1.03-7.32)。目前形势没有出现时间演变。对来自中东国家的航班旅客数据的分析表明,某些地区有很高的输入风险。虽然对全球卫生安全没有立即构成威胁,但这种分析为未来的参考和更新提供了基线情景,建议加强监测以减少漏报,并呼吁在全球高输入风险地区保持警惕。

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Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.中东呼吸综合征冠状病毒(MERS-CoV)在中东的流行评估及采用新型最大似然分析方法评估国际传播风险。
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