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dc.contributor.advisorReynolds, Kelly A.
dc.contributor.authorWilson, Amanda Marie
dc.creatorWilson, Amanda Marie
dc.date.accessioned2018-06-27T22:15:37Z
dc.date.available2018-06-27T22:15:37Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10150/628167
dc.description.abstractIntroduction: Mitigating nosocomial infections continues to be a current challenge for infection control professionals. Understanding how human behavior, especially the hand hygiene compliance of healthcare workers, and cleaning interventions affect infection risks would allow for optimization of current risk mitigation strategies. Mathematical modeling has been applied in healthcare contexts to understand the mechanisms of infection transmission, but few mechanistic models exist that account for second-by-second contacts with surfaces that may result in exposures and infection. Among existing models, few address viral exposures specifically. The purpose of these studies was to use existing frameworks and develop and validate a viral exposure model with bacteriophage tracer data to estimate infection risks and the efficacies of hand washing and surface cleaning interventions Methods: A viral exposure model assuming a steady state viral concentration on hands was used to estimate rotavirus, rhinovirus, and influenza A virus infection risks. The infection risk reduction associated with a viral reduction from a single surface cleaning was estimated. The viral reduction on surfaces measured from a single cleaning with an EPA-registered surface disinfectant in a bacteriophage tracer study was used to represent the expected viral reduction on surfaces. Infection risk reductions for 99%, 99.9%, 99.99%, and 99.999% viral reductions on surfaces and the reductions on surfaces necessary to meet a variety of risk targets were also estimated. Using data from the same bacteriophage tracer study, a discrete event model that accounted for non-steady-state viral concentrations was developed. Bacteriophage concentrations on surfaces and on nurse hands were collected during the tracer study conducted in an urgent care. A lognormal distribution was fit to measured viral surface concentrations from the tracer study. The model was validated by comparing estimated viral concentrations on hands at the end of the simulated exposure with measured viral concentrations on nurse hands. After validation, the model was used to estimate the infection risk reductions for a 15% increase in hand hygiene compliance and for 1 and 2 surface cleanings. Results: Using a percent reduction of viruses on surfaces observed in a bacteriophage tracer study (94.1%), median infection risks from a single contact with a fomite were reduced by 94.1%. For six hours of contacts, median infection risks were reduced by 92.96% - 94.1%. Surface concentration and infection risk parameters were highly correlated. To achieve a risk of one in a million for rotavirus and rhinovirus, >99.99% viral surface reduction would be needed. The discrete event model developed with bacteriophage tracer data was validated, as all measured viral concentrations on nurse hands fell within the distributions of predicted viral concentrations on hands. All Wilcoxon Rank Sum tests comparing measured virus concentrations on nurse hands to those that were predicted were not statistically significant (α=0.05), indicating that the distribution of model-predicted and experimentally measured viral concentrations were not statistically significantly different. Using the discrete event model, a single cleaning and a 15% increase in hand hygiene were predicted to lower rotavirus, rhinovirus, and infection A viral infection risks by 5.6% - 17.4% and 6.5% - 20.4%, respectively. Two surface cleanings decreased predicted infection risks by 12.9% to 35.6%. The discrete event model predicted higher baseline infection risks than the steady state model. Discussion: Using bacteriophage tracer studies to inform current exposure models or to develop and validate exposure models is a novel approach that can be used in future studies for cleaning protocol optimization. Both exposure models used in these studies reaffirm the importance of surface cleaning in mitigating infection risk. The discrete event model demonstrates the importance of surface cleaning and increased hand hygiene compliance in lowering infection risk from fomite-mediated exposures.en_US
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
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 or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjecthealthcareen_US
dc.subjectmodelingen_US
dc.subjectrisk assessmenten_US
dc.subjectsimulationen_US
dc.subjectvirusen_US
dc.titleModeling Viral Exposures and Infection Risk in Healthcare Settingsen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.contributor.committeememberCanales, Robert A.
dc.contributor.committeememberVerhougstraete, Marc P.
dc.description.releaseRelease after 10-May-2019en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEnvironmental Health Sciencesen_US
thesis.degree.nameM.S.en_US


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