Acta Geographica Sinica ›› 2007, Vol. 62 ›› Issue (2): 157-170.doi: 10.11821/xb200702005

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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

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