Modelling the effect of urbanization on the transmission of an infectious disease

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Modelling the effect of urbanization on the transmission of an infectious disease. / Zhang, Ping; Atkinson, Peter M.
In: Mathematical Biosciences, Vol. 211, No. 1, 01.2008, p. 166-185.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Zhang, P & Atkinson, PM 2008, 'Modelling the effect of urbanization on the transmission of an infectious disease', Mathematical Biosciences, vol. 211, no. 1, pp. 166-185. https://doi.org/10.1016/j.mbs.2007.10.007

APA

Zhang, P., & Atkinson, P. M. (2008). Modelling the effect of urbanization on the transmission of an infectious disease. Mathematical Biosciences, 211(1), 166-185. https://doi.org/10.1016/j.mbs.2007.10.007

Vancouver

Zhang P, Atkinson PM. Modelling the effect of urbanization on the transmission of an infectious disease. Mathematical Biosciences. 2008 Jan;211(1):166-185. Epub 2007 Nov 4. doi: 10.1016/j.mbs.2007.10.007

Author

Zhang, Ping ; Atkinson, Peter M. / Modelling the effect of urbanization on the transmission of an infectious disease. In: Mathematical Biosciences. 2008 ; Vol. 211, No. 1. pp. 166-185.

Bibtex

@article{f966e9c22ab7407383d7fc2b8406bf23,

title = "Modelling the effect of urbanization on the transmission of an infectious disease",

abstract = "This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.",

keywords = "CA land use development model, Population projection matrix model, CA epidemic model, Urbanization, Infectious disease transmission",

author = "Ping Zhang and Atkinson, {Peter M.}",

note = "M1 - 1",

year = "2008",

month = jan,

doi = "10.1016/j.mbs.2007.10.007",

language = "English",

volume = "211",

pages = "166--185",

journal = "Mathematical Biosciences",

issn = "0025-5564",

publisher = "Elsevier Inc.",

number = "1",

}

RIS

TY - JOUR

T1 - Modelling the effect of urbanization on the transmission of an infectious disease

AU - Zhang, Ping

AU - Atkinson, Peter M.

N1 - M1 - 1

PY - 2008/1

Y1 - 2008/1

N2 - This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

AB - This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

KW - CA land use development model

KW - Population projection matrix model

KW - CA epidemic model

KW - Urbanization

KW - Infectious disease transmission

U2 - 10.1016/j.mbs.2007.10.007

DO - 10.1016/j.mbs.2007.10.007

M3 - Journal article

VL - 211

SP - 166

EP - 185

JO - Mathematical Biosciences

JF - Mathematical Biosciences

SN - 0025-5564

IS - 1

ER -

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