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本文引用的文献

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J Theor Biol. 2004 Apr 7;227(3):369-79. doi: 10.1016/j.jtbi.2003.11.014.
2
Epidemiology. Modeling the SARS epidemic.流行病学。非典疫情建模。
Science. 2003 Jun 20;300(5627):1884-5. doi: 10.1126/science.1086925. Epub 2003 May 23.
3
Transmission dynamics and control of severe acute respiratory syndrome.严重急性呼吸综合征的传播动力学与控制
Science. 2003 Jun 20;300(5627):1966-70. doi: 10.1126/science.1086616. Epub 2003 May 23.
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Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions.香港严重急性呼吸系统综合症病原体的传播动态:公共卫生干预措施的影响
Science. 2003 Jun 20;300(5627):1961-6. doi: 10.1126/science.1086478. Epub 2003 May 23.
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A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods.使用马尔可夫链蒙特卡罗方法对随机流行病模型进行贝叶斯推断的教程介绍。
Math Biosci. 2002 Nov-Dec;180:103-14. doi: 10.1016/s0025-5564(02)00109-8.
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A general model for stochastic SIR epidemics with two levels of mixing.具有两级混合的随机SIR流行病通用模型。
Math Biosci. 2002 Nov-Dec;180:73-102. doi: 10.1016/s0025-5564(02)00125-6.
7
Subcritical endemic steady states in mathematical models for animal infections with incomplete immunity.具有不完全免疫的动物感染数学模型中的亚临界地方病稳态
Math Biosci. 2000 May;165(1):1-25. doi: 10.1016/s0025-5564(00)00012-2.
8
Perspective: human contact patterns and the spread of airborne infectious diseases.观点:人际接触模式与空气传播传染病的传播
Trends Microbiol. 1999 Sep;7(9):372-7. doi: 10.1016/s0966-842x(99)01546-2.
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Some properties of an estimator for the basic reproduction number of the general epidemic model.
Math Biosci. 1999 Jun;159(1):79-96. doi: 10.1016/s0025-5564(99)00009-7.
10
Correlation models for childhood epidemics.儿童流行病的相关模型。
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亚洲非典病例的爆发模式。

The outbreak pattern of the SARS cases in Asia.

作者信息

Zhang Zhibin, Sheng Chengfa, Ma Zufei, Li Dianmo

机构信息

Institute of Zoology, Chinese Academy of Sciences, 100080 Beijing, China.

出版信息

Chin Sci Bull. 2004;49(17):1819-1823. doi: 10.1007/BF03183407.

DOI:10.1007/BF03183407
PMID:32214712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7089107/
Abstract

The severe acute respiratory syndrome (SARS) caused tremendous damage to many Asia countries, especially China. The transmission process and outbreak pattern of SARS is still not well understood. This study aims to find a simple model to describe the outbreak pattern of SARS cases by using SARS case data commonly released by governments. The outbreak pattern of cumulative SARS cases is expected to be a logistic type because the infection will be slowed down due to the increasing control effort by people and/or due to depletion of susceptible individuals. The increase rate of SARS cases is expected to decrease with the cumulative SARS cases, as described by the traditional logistical model, which is widely used in population dynamic studies. The instantaneous rate of increases were significantly and negatively correlated with the cumulative SARS cases in mainland of China (including Beijing, Hebei, Tianjin, Shanxi, the Autonomous Region of Inner Mongolia) and Singapore. The basic reproduction number in Asia ranged from 2.0 to 5.6 (except for Taiwan, China). The of Hebei and Tianjin were much higher than that of Singapore, Hongkong, Beijing, Shanxi, Inner Mongolia, indicating SARS virus might have originated differently or new mutations occurred during transmission. We demonstrated that the outbreaks of SARS in many regions of Asia were well described by the logistic model, and the control measures implemented by governments are effective. The maximum instantaneous rate of increase, basic reproductive number, and maximum cumulative SARS cases were also calculated by using the logistic model.

摘要

严重急性呼吸综合征(SARS)给许多亚洲国家,尤其是中国造成了巨大破坏。SARS的传播过程和爆发模式仍未得到充分了解。本研究旨在通过使用政府通常公布的SARS病例数据,找到一个简单模型来描述SARS病例的爆发模式。由于人们加强防控努力和/或易感个体数量减少,SARS累计病例的爆发模式预计为逻辑斯蒂型,感染速度将会放缓。正如传统逻辑斯蒂模型所描述的那样,SARS病例的增长率预计会随着SARS累计病例数的增加而下降,该模型在种群动态研究中被广泛应用。在中国内地(包括北京、河北、天津、山西、内蒙古自治区)和新加坡,SARS病例的瞬时增长率与SARS累计病例数呈显著负相关。亚洲地区的基本再生数在2.0至5.6之间(中国台湾地区除外)。河北和天津的基本再生数远高于新加坡、香港、北京、山西、内蒙古,这表明SARS病毒的起源可能不同,或者在传播过程中发生了新的突变。我们证明,逻辑斯蒂模型能够很好地描述亚洲许多地区的SARS疫情爆发情况,并且政府实施的防控措施是有效的。我们还使用逻辑斯蒂模型计算了最大瞬时增长率、基本再生数和最大SARS累计病例数。