An evaluation of parsimony for microbial risk assessment models
dc.contributor.author | Soller, Jeffrey A. | en_US |
dc.contributor.author | Eisenberg, Joseph N. S. | en_US |
dc.date.accessioned | 2008-01-04T20:11:17Z | |
dc.date.available | 2009-02-03T16:28:49Z | en_US |
dc.date.issued | 2008-02 | en_US |
dc.identifier.citation | Soller, Jeffrey A.; Eisenberg, Joseph N. S. (2008). "An evaluation of parsimony for microbial risk assessment models." Environmetrics 19(1): 61-78. <http://hdl.handle.net/2027.42/57535> | en_US |
dc.identifier.issn | 1180-4009 | en_US |
dc.identifier.issn | 1099-095X | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/57535 | |
dc.description.abstract | Microbial risk assessment (MRA) is a process that evaluates the likelihood of adverse human health effects following exposure to a medium in which pathogens are present. Several different classes of models are available to quantitatively characterize risks to human health from exposure to pathogens. Herein, we consider the question of parsimony for specific realizations of representative static and dynamic MRA models and identify conditions under which the more complex dynamic model provides sufficient additional insight to justify the added modeling complexity. To address this question, a standard static individual-level risk model is compared to a deterministic dynamic population-level model that explicitly includes secondary transmission and immunity processes. Exposure parameters are based on a scenario defined by human exposure to pathogens in reclaimed water. A sensitivity analysis is implemented to identify conditions under which static and dynamic models yield substantially different results. Under low risk conditions, defined by a combination of exposure levels and infectivity of the pathogen, the simpler static model provides satisfactory risk estimates. The approach presented here provides a basis for model selection for a broad range of MRA applications. Copyright © 2007 John Wiley & Sons, Ltd. | en_US |
dc.format.extent | 335255 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | John Wiley & Sons, Ltd. | en_US |
dc.subject.other | Mathematics and Statistics | en_US |
dc.title | An evaluation of parsimony for microbial risk assessment models | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Atmospheric, Oceanic and Space Sciences | en_US |
dc.subject.hlbsecondlevel | Civil and Environmental Engineering | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | University of Michigan, Ann Arbor, MI 48104, USA | en_US |
dc.contributor.affiliationother | Soller Environmental, Berkeley, CA 94703, USA ; Soller Environmental, Berkeley, CA 94703, USA. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/57535/1/856_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/env.856 | en_US |
dc.identifier.source | Environmetrics | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.