Department of Biological Sciences and Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
Epidemics. 2009 Dec;1(4):250-8. doi: 10.1016/j.epidem.2009.11.002. Epub 2009 Nov 14.
Mathematical models of infectious disease spread are important tools for assessing the threat of a novel pathogen and offer the best information for mitigating an outbreak. Here we present a metapopulation model of disease spread in Great Britain defined at the level of electoral wards. Using data from the United Kingdom 2001 census and the National Travel Survey to define the amount of travel performed by individuals between wards, we examine the effect of assumptions on the regularity of travel. Routine, daily commuter-type movements, characteristic of the working population are shown to lead to a slower epidemic spread compared to movements with random destinations. We demonstrate that routine movements slow down the epidemic spread compared to a standard metapopulation setting by up to 25%. We also show that spurious long distance movements present in the census data do not have a significant impact on the development of a potential epidemic in Great Britain.
传染病传播的数学模型是评估新型病原体威胁的重要工具，并为减轻疫情提供了最佳信息。在这里，我们提出了一种在选区层面定义的英国疾病传播的复域模型。利用来自英国 2001 年人口普查和全国旅行调查的数据来定义个人在选区之间的旅行量，我们研究了假设对旅行规律性的影响。与具有随机目的地的运动相比，具有日常通勤特征的常规运动导致传染病传播速度较慢。我们证明，与标准复域设置相比，常规运动将传染病的传播速度减慢了 25%。我们还表明，人口普查数据中存在的虚假长途运动对英国潜在疫情的发展没有重大影响。
