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2019新型冠状病毒传播风险评估及其对公共卫生干预措施的启示

Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions.

作者信息

Tang Biao, Wang Xia, Li Qian, Bragazzi Nicola Luigi, Tang Sanyi, Xiao Yanni, Wu Jianhong

机构信息

The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, China.

Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada.

出版信息

J Clin Med. 2020 Feb 7;9(2):462. doi: 10.3390/jcm9020462.

Abstract

Since the emergence of the first cases in Wuhan, China, the novel coronavirus (2019-nCoV) infection has been quickly spreading out to other provinces and neighboring countries. Estimation of the basic reproduction number by means of mathematical modeling can be helpful for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity. A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. The estimations based on likelihood and model analysis show that the control reproduction number may be as high as 6.47 (95% CI 5.71-7.23). Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction adopted by Wuhan on 2019-nCoV infection in Beijing being almost equivalent to increasing quarantine by a 100 thousand baseline value. It is essential to assess how the expensive, resource-intensive measures implemented by the Chinese authorities can contribute to the prevention and control of the 2019-nCoV infection, and how long they should be maintained. Under the most restrictive measures, the outbreak is expected to peak within two weeks (since 23 January 2020) with a significant low peak value. With travel restriction (no imported exposed individuals to Beijing), the number of infected individuals in seven days will decrease by 91.14% in Beijing, compared with the scenario of no travel restriction.

摘要

自中国武汉出现首例病例以来,新型冠状病毒(2019 - nCoV)感染已迅速蔓延至其他省份及周边国家。通过数学建模估算基本再生数有助于确定疫情的潜在规模和严重程度,并为确定疾病干预措施的类型和强度提供关键信息。基于疾病的临床进展、个体的流行病学状况及干预措施设计了一个确定性 compartmental 模型。基于似然性和模型分析的估计表明,控制再生数可能高达6.47(95%置信区间5.71 - 7.23)。敏感性分析表明,诸如强化接触者追踪并随后进行隔离等干预措施可有效降低控制再生数和传播风险,武汉实施的旅行限制措施对北京2019 - nCoV感染的影响几乎等同于将隔离人数在基线值基础上增加10万。评估中国当局实施的这些昂贵且资源密集型措施如何有助于2019 - nCoV感染的防控以及应维持多长时间至关重要。在最严格的措施下,疫情预计将在两周内(自2020年1月23日起)达到峰值,且峰值显著较低。与无旅行限制的情况相比,实施旅行限制(无输入性暴露个体进入北京)后,北京七天内的感染人数将减少91.14%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b18f/7074281/50974342b873/jcm-09-00462-g001.jpg

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