地理学报 ›› 2007, Vol. 62 ›› Issue (2): 157-170.doi: 10.11821/xb200702005

• 城市发展 • 上一篇    下一篇

城市化对传染病传播影响的动态模拟 ———以英国南安普顿市为例

张萍1,2,3, 张柏1, Peter M. Atkinson4   

  1. 1. 中国科学院东北地理与农业生态研究所, 长春130012;
    2. 中国科学院研究生院, 北京100039;
    3. 吉林大学地球探测科学与技术学院, 长春130026;
    4. Department of Geography, University of Southampton, Southampton SO17 1BJ, UK
  • 收稿日期:2006-10-13 修回日期:2006-11-30 出版日期:2007-02-25 发布日期:2010-08-04
  • 作者简介:张萍(1972-), 女, 博士研究生, 讲师, 主要从事地理建模、空间分析研究。E-mail: gracezp2004@yahoo.com.cn
  • 基金资助:

    国家留学基金委员会留学基金资助项目(2003822089)

Modelling Framework on Urbanization' s Effect on the Infectious Disease Transmission: A Case Study on Southampton of UK

ZHANG Ping1,2,3, ZHANG Bai1, Peter M. ATKINSON4   

  1. 1. Northeast Institute of Geography and Agricultural Ecology, CAS, Changchun 130012, China;
    2. Graduate School of the Chinese Academy of Sciences, Beijing 100039, China;
    3. Geo-Exploration Science & Technology College, Jilin University, Changchun 130026, China;
    4. Department of Geography, University of Southampton, Southampton SO17 1BJ, UK
  • Received:2006-10-13 Revised:2006-11-30 Online:2007-02-25 Published:2010-08-04
  • Supported by:

    Fund from The China Scholarship Council, No.2003822089

摘要:

在定量化和空间化模拟分析的基础上, 探讨了城市化对传染病传播影响的模型框架。该模型框架是通过人口空间分布表面, 集成了元胞自动机土地开发模型、人口预测矩阵模型和 元胞自动机传染病模型, 在动态的, 随机的模拟环境中将城市化与传染病传播结合起来。以英国南安普顿市为研究区, 对南安普顿市的“郊区化”对传染病传播的影响进行了动态模拟, 场景模拟和定量分析。结果表明: 4 个模拟预测年期(2001 年、2011 年、2021 年和2031 年) 的平均传染病例数没有太大的变化, “郊区化”对传染病的传播没有太大影响。但是, “郊 区化”中的城市局部的家庭迁移和全市的年轻年龄组的迁移可能会通过在同年份减少平均传染病例数而影响传染病的传播。

关键词: 城市化, 传染病传播, 元胞自动机土地开发模型, 人口预测矩阵模型, 元胞自动机传染病模型, 英国

Abstract:

This paper presents a modelling framework to model the effect of urbanization on the transmission of infectious disease, which integrates a CA land use development model, population projection matrix model and CA epidemic model by population surface modelling, allowing to analyze its simulation results in a quantitative and spatial way. Its creative feature is combining urbanization, population projection in age-structure with infectious disease transmission in a dynamic, stochastic modelling environment, so it can shed light on providing the relationship between urbanization and infectious disease transmission, which could not be realized by equilibrium or analytical methods. A case study is presented involving modelling influenza transmission in a dynamically evolving city, Southampton, UK. Preliminary results show that the average number of infection cases in years (2001, 2011, 2021 and 2031) has no big difference from each other and suburbanization has very little impact on the infection disease transmission. Moreover, simulation scenario is a useful way to explore the effects of families' movements in part of the city and age-group 20-24 moving out of Southampton on infectious disease transmission here. Its results have the possibility to reflect that both the families' movements in part of the city and age-group 20-24 moving out of Southampton can influence the infectious disease transmission by decreasing the average number of infection cases in the same year.

Key words: urbanization, infectious disease transmission, CA land use development model, population projection matrix model, CA epidemic model, UK