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一个用于评估室内空气传播感染风险的概率传播动力学模型。

A probabilistic transmission dynamic model to assess indoor airborne infection risks.

作者信息

Liao Chung-Min, Chang Chao-Fang, Liang Huang-Min

机构信息

Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617, ROC.

出版信息

Risk Anal. 2005 Oct;25(5):1097-107. doi: 10.1111/j.1539-6924.2005.00663.x.

Abstract

The purpose of this article is to quantify the public health risk associated with inhalation of indoor airborne infection based on a probabilistic transmission dynamic modeling approach. We used the Wells-Riley mathematical model to estimate (1) the CO2 exposure concentrations in indoor environments where cases of inhalation airborne infection occurred based on reported epidemiological data and epidemic curves for influenza and severe acute respiratory syndrome (SARS), (2) the basic reproductive number, R0 (i.e., expected number of secondary cases on the introduction of a single infected individual in a completely susceptible population) and its variability in a shared indoor airspace, and (3) the risk for infection in various scenarios of exposure in a susceptible population for a range of R0. We also employ a standard susceptible-infectious-recovered (SIR) structure to relate Wells-Riley model derived R0 to a transmission parameter to implicate the relationships between indoor carbon dioxide concentration and contact rate. We estimate that a single case of SARS will infect 2.6 secondary cases on average in a population from nosocomial transmission, whereas less than 1 secondary infection was generated per case among school children. We also obtained an estimate of the basic reproductive number for influenza in a commercial airliner: the median value is 10.4. We suggest that improving the building air cleaning rate to lower the critical rebreathed fraction of indoor air can decrease transmission rate. Here, we show that virulence of the organism factors, infectious quantum generation rates (quanta/s by an infected person), and host factors determine the risk for inhalation of indoor airborne infection.

摘要

本文的目的是基于概率传播动态建模方法,对与吸入室内空气传播感染相关的公共卫生风险进行量化。我们使用威尔斯 - 莱利数学模型来估计:(1)根据报告的流行病学数据以及流感和严重急性呼吸综合征(SARS)的流行曲线,在发生吸入性空气传播感染病例的室内环境中的二氧化碳暴露浓度;(2)基本再生数R0(即在完全易感人群中引入单个感染个体时预期的二代病例数)及其在共享室内空间中的变异性;(3)在一系列R0值下,易感人群在各种暴露场景中的感染风险。我们还采用标准的易感 - 感染 - 康复(SIR)结构,将威尔斯 - 莱利模型得出的R0与一个传播参数相关联,以阐明室内二氧化碳浓度与接触率之间的关系。我们估计,在医院传播中,单个SARS病例平均会感染2.6个二代病例,而在校儿童中每个病例产生的二代感染少于1例。我们还获得了商用客机上流感基本再生数的估计值:中位数为10.4。我们建议提高建筑物空气净化率以降低室内空气的临界再呼吸分数,从而降低传播率。在此,我们表明病原体因素的毒力、感染量子产生率(感染者每秒产生的量子数)和宿主因素决定了吸入室内空气传播感染的风险。

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