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dc.contributor.advisorChoi, Christopher
dc.contributor.authorBalagopal, Tulika C.
dc.creatorBalagopal, Tulika C.
dc.date.accessioned2019-07-06T02:20:05Z
dc.date.available2019-07-06T02:20:05Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10150/633307
dc.description.abstractCryptosporidiosis is a common gastrointestinal disease that significantly impacts immune-compromised individuals. In this study, water quality analysis and doseresponse models are used to calculate the location-based risk of Cryptosporidium infection within 24 hours of an intrusion into a drinking water system. Current water quality models such as EP ANET are based upon two main assumptions: complete mixing occurs at pipe cross junctions, and axial dispersion of a solute does not occur along the length of a pipe. To improve the accuracy of EPANET, two newly developed models, AZRED I and II, consider these assumptions. EP ANET-generated simulations model plug flow-the movement of large contaminant concentration pulses with respect to time-while AZRED-generated simulations model solute dispersion, which results in lower contaminant concentrations over a longer period of time. The risk of infection was calculated for populations at four specific locations in a network using an exponential model. Results obtained using AZRED, when compared to results obtained from EPANET, predicted a higher risk of infection at downstream locations.
dc.language.isoen
dc.publisherThe University of Arizona.
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
dc.titleQuantitative Microbial Risk Assessment Using Azred Water Quality Models
dc.typetext
dc.typeReport-Reproduction (electronic)
thesis.degree.grantorUniversity of Arizona
thesis.degree.levelmasters
dc.contributor.committeemember
thesis.degree.disciplineBiomedical Engineering
thesis.degree.nameM.S.
dc.description.noteDigitized from a paper copy provided by the Physiological Sciences Graduate Interdisciplinary Program.
refterms.dateFOA2019-07-06T02:20:05Z


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