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Mathematical Modelling of the Epidemiology of Tuberculosis

  • Peter J. White
  • Geoff P. Garnett
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 673)

Abstract

Despite the infectious agent that causes tuberculosis having been discovered in 1882, many aspects of the natural history and transmission dynamics of TB are still not fully understood. This is reflected in differences in the structures of mathematical models of TB, which in turn produce differences in the predicted impacts of interventions. Gaining a greater understanding of TB transmission dynamics requires further empirical laboratory and field work, mathematical modelling and interaction between them. Modelling can be used to quantify uncertainty due to different gaps in our knowledge to help identify research priorities. Fortunately, the present moment is an exciting time for TB epidemiology, with rapid progress being made in applying new mathematical modelling techniques, new tools for TB diagnosis and genetic analysis and a growing interest in developing more-effective public-health interventions.

Keywords

Latent Infection Tuberculosis Control Isoniazid Preventive Therapy Bull World Health Organ Theor Popul Biol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Landes Bioscience and Springer Science+Business Media 2010

Authors and Affiliations

  • Peter J. White
    • 1
    • 2
  • Geoff P. Garnett
    • 2
  1. 1.Modelling and Economics Unit, Health Protection Agency Centre for InfectionsLondonUK
  2. 2.MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of MedicineImperial College LondonLondonUK

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