IDEAS home Printed from
   My bibliography  Save this article

Inferring Infection Transmission Parameters That Influence Water Treatment Decisions


  • Stephen E. Chick

    () (Technology Management Area, INSEAD, Boulevard de Constance, 77305 Fontainebleau CEDEX, France)

  • Sada Soorapanth

    () (Department of Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, Michigan 48109)

  • James S. Koopman

    () (Department of Epidemiology, School of Public Health-I, and Center for the Study of Complex Systems, University of Michigan, 109 Observatory Street, Ann Arbor, Michigan 48109)


One charge of the United States Environmental Protection Agency is to study the risk of infection for microbial agents that can be disseminated through drinking water systems, and to recommend water treatment policy to counter that risk. Recently proposed dynamical system models quantify indirect risks due to secondary transmission, in addition to primary infection risk from the water supply considered by standard assessments. Unfortunately, key parameters that influence water treatment policy are unknown, in part because of lack of data and effective inference methods. This paper develops inference methods for those parameters by using stochastic process models to better incorporate infection dynamics into the inference process. Our use of endemic data provides an alternative to waiting for, identifying, and measuring an outbreak. Data both from simulations and from New York City illustrate the approach.

Suggested Citation

  • Stephen E. Chick & Sada Soorapanth & James S. Koopman, 2003. "Inferring Infection Transmission Parameters That Influence Water Treatment Decisions," Management Science, INFORMS, vol. 49(7), pages 920-935, July.
  • Handle: RePEc:inm:ormnsc:v:49:y:2003:i:7:p:920-935

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. anonymous, 2000. "Annual report highlights the Atlanta Fed at work," Financial Update, Federal Reserve Bank of Atlanta, issue Jul, pages 1-5.
    2. Anonymous, 2000. "Annual Report On Cotton Economics Research 1999/00," Cotton Economics Research Institute CER Series 31253, Texas Tech University, Department of Agricultural and Applied Economics.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:49:y:2003:i:7:p:920-935. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.