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Influenza A （HIN1） transmission by road traffic between cities and towns

ISSN号：1005-4529
期刊名称：《中华医院感染学杂志》
时间：0
分类：U491[交通运输工程—交通运输规划与管理;交通运输工程—道路与铁道工程] TN929.11[电子电信—通信与信息系统;电子电信—信息与通信工程]
作者机构：[1]College of Resources and Environment Science, Hunan Normal University, Changsha 410081, China, [2]Peking University Health Science Center, Beijing 100191, China, [3]Changsha Municipal Center for Disease Prevention and Control, Changsha 410001, China, [4]State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Science, Beijing 100071, China, [5]School of Mechanical, Electronic and Information Engineering, China University of Mining and Technology (Beijing Campus), Beifing 100083, China
相关基金：We wish to express our thanks to the anonymous referees for their helpful comments on an earlier draft of this article. This work was supported by the Key Discipline Construction Project in Hunan Province （2008001）, and the Science and Technology Planning Project of Hunan Province, China （2010SK3007）.

作者： XIAO Hong[1], TIAN HuaiYu[1], ZHAO Jian[2], ZHANG XiXing[3], LI YaPin[4], LIU Yi[5], LIU RuChun[3], CHEN TianMu[3]

关键词：道路交通, 城市化, 传输, 城镇, 流感, 疾病传播, A型, 模型模拟, influenza A （H1N1）, road traffic, spatiotemporal transmission, incidence rate, risk factors

中文摘要：

流行性感冒 A (H1N1 ) 被道路交通在城市和镇之间广泛地散布并且在 2009 在中国在公共健康上有主要影响。它的传播的理解规定具有有进行中的都市化并且为由流行病的损坏的缓解的大意义。我们分析了沿着在长沙的道路的空间与时间的传播和风险因素，和联合散开速度和流动人口缩放构造一个流行散开模型模仿它在城市和镇之间的传播的流行性感冒 A (H1N1 ) 。结果证明沿着高速公路和道路交叉的区域让更高的发生比另外的区域评价。分别地，高速公路和县道路在快速的发展阶段和流行山峰起了一个重要作用，城市间的公共汽车车站显示出疾病传播的高风险。模型在城市和镇里模仿疾病爆发的紧张和中心，并且提供疾病的更完全的模拟空间与时间的过程比另外的模型。

英文摘要：

Influenza A （H1N1） was spread widely between cities and towns by road traffic and had a major impact on public health in China in 2009. Understanding regulation of its transmission is of great significance with urbanization ongoing and for mitigation of damage by the epidemic. We analyzed influenza A （H1N1） spatiotemporal transmission and risk factors along roads in Changsha, and combined diffusion velocity and floating population size to construct an epidemic diffusion model to simulate its transmission between cities and towns. The results showed that areas along the highways and road intersections had a higher incidence rate than other areas. Expressways and county roads played an important role in the rapid development stage and the epidemic peak, respectively, and intercity bus stations showed a high risk of disease transmission. The model simulates the intensity and center of disease outbreaks in cities and towns, and provides a more complete simulation of the disease spatiotemporal process than other models.

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