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Operations Research and Health Care pp 465–491Cite as

Microbial Risk Assessment for Drinking Water

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 70))

Summary

Infectious microbes can be transmitted through the drinking water supply. Recent research indicates that infection transmission dynamics influence the public health benefit of water treatment interventions, although some risk assessments currently in use do not fully account for those dynamics. This chapter models the public health benefit of two interventions: improvements to centralized water treatment facilities, and localized point-of-use treatments in the homes of particularly susceptible individuals. A sensitivity analysis indicates that the best option is not as obvious as that suggested by an analysis that ignores infection dynamics suggests. Deterministic and stochastic dynamic systems models prove to be useful tools for assessing the dynamics of risk exposure.

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Author information

Authors and Affiliations

  1. Technology Management Area Fontainebleau, INSEAD, France

    Stephen E. Chick

  2. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, 48109

    Sada Soorapanth

  3. Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109

    James S. Koopman

  4. Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, 48109

    James S. Koopman

Authors
  1. Stephen E. Chick
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  2. Sada Soorapanth
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  3. James S. Koopman
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Editor information

Editors and Affiliations

  1. Stanford University, USA

    Margaret L. Brandeau

  2. Georgia Institute of Technology, USA

    François Sainfort

  3. University of California at Los Angeles, USA

    William P. Pierskalla

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© 2005 Springer Science + Business Media, Inc.

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Chick, S.E., Soorapanth, S., Koopman, J.S. (2005). Microbial Risk Assessment for Drinking Water. In: Brandeau, M.L., Sainfort, F., Pierskalla, W.P. (eds) Operations Research and Health Care. International Series in Operations Research & Management Science, vol 70. Springer, Boston, MA. https://doi.org/10.1007/1-4020-8066-2_18

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  • DOI: https://doi.org/10.1007/1-4020-8066-2_18

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7629-9

  • Online ISBN: 978-1-4020-8066-1

  • eBook Packages: Springer Book Archive

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