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Sensitivity Analysis in Infectious Disease Control

  • Norman T. J. Bailey
  • J. L. Duppenthaler
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 5)

Abstract

The use of comparatively simple multi-state, multi-parameter models has been developed in recent years both to promote epidemiological understanding and to guide public health control of a variety of infectious diseases. Applications have been made to a wide range of bacterial diseases like tuberculosis, typhoid fever, cholera, tetanus, leprosy, etc.; virus diseases like measles, influenza, infectious hepatitis, and poliomyelitis; venereal diseases, especially gonorrhoea; and parasitic diseases such as malaria and schistosomiasis (see Bailey, 1975).

Keywords

Infectious Hepatitis Typhoid Fever Resource Allocation Model Infectious Disease Control Matrix Manipulation 
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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References

  1. Bailey, N.T.J. (1975). The Mathematical Theory of Infectious Diseases. London: Griffin.Google Scholar
  2. Bekessy, A. (1971). Remarks relevant to the paper: Epidemiological model of typhoid fever etc. (Internal WHO memorandum, 24/9/71).Google Scholar
  3. Brauer, F. and Nohel, J.A. (1969). Qualitative Theory of Ordinary Differential Equations. New York: Benjamin.Google Scholar
  4. Cruz, Jr., J.B. (Ed.) (1973). System Sensitivity Analysis. Stroudsburg, Pennsylvania: Dowden, Hutchinson & Ross.Google Scholar
  5. Mehra, R.K. and Lainiotis, D.G. (Eds.) (1976). System Identification: Advances and Case Studies. London: Academic Press.Google Scholar
  6. Mesarovic, M. and Pestel, E. (1975). Mankind at the Turning Point. London: Hutchinson.Google Scholar
  7. Tomovic, R. and Vukobratovic, M. (1972). General Sensitivity Theory, New York: American Elsevier.Google Scholar

Copyright information

© Online Conferences Ltd., Uxbridge, England 1979

Authors and Affiliations

  • Norman T. J. Bailey
    • 1
  • J. L. Duppenthaler
    • 1
  1. 1.Unit of Health Statistical MethodologyWHOGenevaSwitzerland

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