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1918年瑞士日内瓦大流感疫情的传播动态:评估假设干预措施的效果。

Transmission dynamics of the great influenza pandemic of 1918 in Geneva, Switzerland: Assessing the effects of hypothetical interventions.

作者信息

Chowell G, Ammon C E, Hengartner N W, Hyman J M

机构信息

Theoretical Division (MS B284), Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

出版信息

J Theor Biol. 2006 Jul 21;241(2):193-204. doi: 10.1016/j.jtbi.2005.11.026. Epub 2006 Jan 4.

DOI:10.1016/j.jtbi.2005.11.026
PMID:16387331
Abstract

Recurrent outbreaks of the avian H5N1 influenza virus in Asia represent a constant global pandemic threat. We characterize and evaluate hypothetical public health measures during the 1918 influenza pandemic in the Canton of Geneva, Switzerland. The transmission rate, the recovery rate, the diagnostic rate, the relative infectiousness of asymptomatic cases, and the proportion of clinical cases are estimated through least-squares fitting of the model to epidemic curve data of the cumulative number of hospital notifications. The latent period and the case fatality proportion are taken from published literature. We determine the variance and identifiability of model parameters via a simulation study. Our epidemic model agrees well with the observed epidemic data. We estimate the basic reproductive number for the spring wave R1;=1.49 (95% CI: 1.45-1.53) and the reproductive number for the fall wave R2;=3.75 (95% CI: 3.57-3.93). In addition, we estimate the clinical reporting for these two waves to be 59.7% (95% CI: 55.7-63.7) and 83% (95% CI: 79-87). We surmise that the lower reporting in the first wave can be explained by a lack of initial awareness of the epidemic and the relative higher severity of the symptoms experienced during the fall wave. We found that effective isolation measures in hospital clinics at best would only ensure control with probability 0.87 while reducing the transmission rate by >76.5% guarantees stopping an epidemic.

摘要

亚洲地区H5N1禽流感病毒的反复爆发对全球构成了持续的大流行威胁。我们对瑞士日内瓦州1918年流感大流行期间的假设性公共卫生措施进行了特征描述和评估。通过将模型与医院通报累积数量的流行曲线数据进行最小二乘拟合,估计了传播率、康复率、诊断率、无症状病例的相对传染性以及临床病例的比例。潜伏期和病死率取自已发表的文献。我们通过模拟研究确定了模型参数的方差和可识别性。我们的流行模型与观察到的流行数据吻合良好。我们估计春季波的基本再生数R1 = 1.49(95%置信区间:1.45 - 1.53),秋季波的再生数R2 = 3.75(95%置信区间:3.57 - 3.93)。此外,我们估计这两波疫情的临床报告率分别为59.7%(95%置信区间:55.7 - 63.7)和83%(95%置信区间:79 - 87)。我们推测,第一波报告率较低的原因可能是对疫情缺乏初步认识,以及秋季波期间出现的症状相对更为严重。我们发现医院诊所采取的有效隔离措施充其量只能以0.87的概率确保疫情得到控制,而将传播率降低76.5%以上才能保证疫情停止。

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