共 95 条
Mathematical models of infectious disease transmission
被引:434
作者:

Grassly, Nicholas C.
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机构:
Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, Ctr Outbreak Anal & Modelling, MRC, London W2 1PG, England Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, Ctr Outbreak Anal & Modelling, MRC, London W2 1PG, England

Fraser, Christophe
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Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, Ctr Outbreak Anal & Modelling, MRC, London W2 1PG, England Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, Ctr Outbreak Anal & Modelling, MRC, London W2 1PG, England
机构:
[1] Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, Ctr Outbreak Anal & Modelling, MRC, London W2 1PG, England
基金:
英国医学研究理事会;
关键词:
D O I:
10.1038/nrmicro1845
中图分类号:
Q93 [微生物学];
学科分类号:
071005 ;
100705 ;
摘要:
Mathematical analysis and modelling is central to infectious disease epidemiology. Here, we provide an intuitive introduction to the process of disease transmission, how this stochastic process can be represented mathematically and how this mathematical representation can be used to analyse the emergent dynamics of observed epidemics. Progress in mathematical analysis and modelling is of fundamental importance to our growing understanding of pathogen evolution and ecology. The fit of mathematical models to surveillance data has informed both scientific research and health policy. This Review is illustrated throughout by such applications and ends with suggestions of open challenges in mathematical epidemiology.
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页码:477 / 487
页数:11
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