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2014年春季沙特阿拉伯中东呼吸综合征冠状病毒疫情的繁殖数和病死率估计:基于公开数据的见解

Estimation of MERS-Coronavirus Reproductive Number and Case Fatality Rate for the Spring 2014 Saudi Arabia Outbreak: Insights from Publicly Available Data.

作者信息

Majumder Maimuna S, Rivers Caitlin, Lofgren Eric, Fisman David

机构信息

Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA.

出版信息

PLoS Curr. 2014 Dec 18;6:ecurrents.outbreaks.98d2f8f3382d84f390736cd5f5fe133c. doi: 10.1371/currents.outbreaks.98d2f8f3382d84f390736cd5f5fe133c.

Abstract

BACKGROUND

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) was initially recognized as a source of severe respiratory illness and renal failure in 2012. Prior to 2014, MERS-CoV was mostly associated with sporadic cases of human illness, of presumed zoonotic origin, though chains of person-to-person transmission in the healthcare setting were reported. In spring 2014, large healthcare-associated outbreaks of MERS-CoV infection occurred in Jeddah and Riyadh, Kingdom of Saudi Arabia. To date the epidemiological information published by public health investigators in affected jurisdictions has been relatively limited. However, it is important that the global public health community have access to information on the basic epidemiological features of the outbreak to date, including the basic reproduction number (R0) and best estimates of case-fatality rates (CFR). We sought to address these gaps using a publicly available line listing of MERS-CoV cases.

METHODS

R0 was estimated using the incidence decay with exponential adjustment ("IDEA") method, while period-specific case fatality rates that incorporated non-attributed death data were estimated using Monte Carlo simulation.

RESULTS

707 cases were available for evaluation. 52% of cases were identified as primary, with the rest being secondary. IDEA model fits suggested a higher R0 in Jeddah (3.5-6.7) than in Riyadh (2.0-2.8); control parameters suggested more rapid reduction in transmission in the former city than the latter. The model accurately projected final size and end date of the Riyadh outbreak based on information available prior to the outbreak peak; for Jeddah, these projections were possible once the outbreak peaked. Overall case-fatality was 40%; depending on the timing of 171 deaths unlinked to case data, outbreak CFR could be higher, lower, or equivalent to pre-outbreak CFR.

CONCLUSIONS

Notwithstanding imperfect data, inferences about MERS-CoV epidemiology important for public health preparedness are possible using publicly available data sources. The R0 estimated in Riyadh appears similar to that seen for SARS-CoV, but CFR appears higher, and indirect evidence suggests control activities ended these outbreaks. These data suggest this disease should be regarded with equal or greater concern than the related SARS-CoV.

摘要

背景

中东呼吸综合征冠状病毒(MERS-CoV)于2012年首次被确认为严重呼吸道疾病和肾衰竭的病因。2014年之前,MERS-CoV大多与散发的人类病例相关,推测为人畜共患病源,尽管有报道称在医疗机构中存在人传人链。2014年春季,沙特阿拉伯王国吉达和利雅得发生了与医疗保健相关的MERS-CoV感染大暴发。迄今为止,受影响辖区的公共卫生调查人员公布的流行病学信息相对有限。然而,全球公共卫生界能够获取有关此次疫情基本流行病学特征的信息非常重要,包括基本再生数(R0)和病死率(CFR)的最佳估计值。我们试图利用公开可得的MERS-CoV病例一览表来填补这些空白。

方法

使用指数调整发病率衰减(“IDEA”)方法估计R0,同时使用蒙特卡罗模拟估计纳入未归因死亡数据的特定时期病死率。

结果

有707例病例可供评估。52%的病例被确定为原发病例,其余为继发病例。IDEA模型拟合表明,吉达的R0(3.5 - 6.7)高于利雅得(2.0 - 2.8);控制参数表明,前者城市的传播下降速度比后者更快。该模型根据疫情高峰前可得的信息准确预测了利雅得疫情的最终规模和结束日期;对于吉达,一旦疫情达到高峰,这些预测就成为可能。总体病死率为40%;根据171例与病例数据无关的死亡时间,疫情病死率可能更高、更低或与疫情前病死率相当。

结论

尽管数据存在缺陷,但利用公开可得的数据源仍有可能推断出对公共卫生防范至关重要的MERS-CoV流行病学情况。利雅得估计的R0似乎与严重急性呼吸综合征冠状病毒(SARS-CoV)的R0相似,但病死率似乎更高,间接证据表明防控活动结束了这些疫情。这些数据表明,应同等或更高度关注这种疾病,与相关的SARS-CoV相比。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0ac/4322060/b59fa01d8c8b/Slide13.jpg

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