Resource title

Inferring infection transmission parameters that influence water treatment decisions

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One charge of the US 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 a 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. The authors' use of endemic data provides an alternative to waiting for, identifying, and measuring an outbreak. Data from both simulations and New York City illustrate the approach.

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en

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application/pdf

Resource resource URL

http://flora.insead.edu/fichiersti_wp/inseadwp2002/2002-108.pdf

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Copyright INSEAD. All rights reserved