Synthesizing data and models for the spread of MERS-CoV, 2013: key role of index cases and hospital transmission.
Synthesizing data and models for the spread of MERS-CoV, 2013: key role of index cases and hospital transmission.
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DOI：
10.1016/j.epidem.2014.09.011
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发表时间：
2014-12
期刊：
影响因子：
3.8
通讯作者：
Viboud C
中科院分区：
文献类型：
--
作者：
Chowell G;Blumberg S;Simonsen L;Miller MA;Viboud C
2013年4月至10月中东呼吸综合征冠状病毒暴发的传播模式。中东呼吸综合征冠状病毒传播模式与指示病例和继发性病例。MERS-CoV传播模式与社区和医院隔离。使用MCMC方法校准MERS-CoV传播模型。数据表明，在2013年疫情的第一阶段，R < 1得到有力支持。截至2014年6月11日，中东呼吸综合征冠状病毒（MERS-CoV）疫情已在阿拉伯半岛造成209人死亡和699例实验室确诊病例。人际传播的性质和强度存在相当大的不确定性，阻碍了防范工作，以前的繁殖数量估计在0.4至1.5之间。本文综合2013年4 - 10月MERS-CoV疫情的流行病学数据和传播模型，在考虑观测偏倚影响的同时，解决疫情风险的不确定性。我们将2013年中东呼吸综合征冠状病毒病例的进展与包含社区和医院隔间的动态传播模型相匹配，并根据人畜共患（指数）病例和继发病例区分传播。假设观察偏倚可以解释所有报告的人畜共患病例都很严重，但只有~ 57%的继发性病例有症状，则中东呼吸综合征冠状病毒的平均繁殖数估计为0.45 （95% CI: 0.29-0.61）。或者，如果仅从表面上看这些流行病学观察结果，则估计指示性病例的传播比继发性病例有效得多(Ri = 0.84 （0.58-1.20) vs Rs = 0.36(0.24-0.51)）。在这两种情况下，医院传播的相对贡献比社区传播的相对贡献高出四倍以上，这表明疾病控制应侧重于住院患者。根据观察偏倚对先前公布的估计进行调整后，证实了对2013年疫情第一阶段平均R < 1的有力支持，因此，中东呼吸综合征冠状病毒继发病例的传播率仍远低于流行阈值。需要更多关于观察过程的信息，以澄清中东呼吸综合征冠状病毒是否本质上在人与人之间传播弱，或者现有的控制措施是否对降低继发性病例的传播力作出了有意义的贡献。我们的研究结果可以帮助评估MERS-CoV近几个月来对疾病监测、控制干预或病毒适应变化的反应。
Transmission models for the MERS-CoV outbreak during April–October 2013. MERS-CoV transmission models with index and secondary cases. MERS-CoV transmission models with community and hospital compartments. Calibration of MERS-CoV transmission models using MCMC methods. Data indicate a strong support for R < 1 in the first stage of the outbreak in 2013. The outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 209 deaths and 699 laboratory-confirmed cases in the Arabian Peninsula as of June 11, 2014. Preparedness efforts are hampered by considerable uncertainty about the nature and intensity of human-to-human transmission, with previous reproduction number estimates ranging from 0.4 to 1.5. Here we synthesize epidemiological data and transmission models for the MERS-CoV outbreak during April–October 2013 to resolve uncertainties in epidemic risk, while considering the impact of observation bias. We match the progression of MERS-CoV cases in 2013 to a dynamic transmission model that incorporates community and hospital compartments, and distinguishes transmission by zoonotic (index) cases and secondary cases. When observation bias is assumed to account for the fact that all reported zoonotic cases are severe, but only ∼57% of secondary cases are symptomatic, the average reproduction number of MERS-CoV is estimated to be 0.45 (95% CI:0.29–0.61). Alternatively, if these epidemiological observations are taken at face value, index cases are estimated to transmit substantially more effectively than secondary cases, (Ri = 0.84 (0.58-1.20) vs Rs = 0.36 (0.24–0.51)). In both scenarios the relative contribution of hospital-based transmission is over four times higher than that of community transmission, indicating that disease control should be focused on hospitalized patients. Adjusting previously published estimates for observation bias confirms a strong support for the average R < 1 in the first stage of the outbreak in 2013 and thus, transmissibility of secondary cases of MERS-CoV remained well below the epidemic threshold. More information on the observation process is needed to clarify whether MERS-CoV is intrinsically weakly transmissible between people or whether existing control measures have contributed meaningfully to reducing the transmissibility of secondary cases. Our results could help evaluate the progression of MERS-CoV in recent months in response to changes in disease surveillance, control interventions, or viral adaptation.
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影响因子：
6.4
作者：
Alagaili AN;Briese T;Mishra N;Kapoor V;Sameroff SC;Burbelo PD;de Wit E;Munster VJ;Hensley LE;Zalmout IS;Kapoor A;Epstein JH;Karesh WB;Daszak P;Mohammed OB;Lipkin WI
通讯作者：
Lipkin WI
影响因子：
9.3
作者：
Chowell G;Simonsen L;Towers S;Miller MA;Viboud C
通讯作者：
Viboud C
影响因子：
56.3
作者：
Cauchemez, Simon;Fraser, Christophe;Van Kerkhove, Maria D.;Donnelly, Christi A.;Riley, Steven;Rambaut, Andrew;Enouf, Vincent;van der Werf, Sylvie;Ferguson, Neil M.
通讯作者：
Ferguson, Neil M.
影响因子：
2.1
作者：
Farrington, CP;Kanaan, MN;Gay, NJ
通讯作者：
Gay, NJ
影响因子：
3.3
作者：
Franks TJ;Chong PY;Chui P;Galvin JR;Lourens RM;Reid AH;Selbs E;McEvoy CP;Hayden CD;Fukuoka J;Taubenberger JK;Travis WD
通讯作者：
Travis WD