Evolving contact networks to analyze epidemic behaviour and studying the effects of vaccination

dc.contributor.advisorAshlock, Daniel
dc.contributor.authorShiller, Elisabeth
dc.date.accessioned2013-01-09T21:04:53Z
dc.date.available2013-01-09T21:04:53Z
dc.date.copyright2013-01
dc.date.created2012-12-05
dc.date.issued2013-01-09
dc.degree.departmentDepartment of Mathematics and Statisticsen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameMaster of Scienceen_US
dc.degree.programmeMathematics and Statisticsen_US
dc.description.abstractEpidemic models help researchers understand and predict the nature of a potential epidemic. This study analyzes and improves network evolution technology that evolves contact networks so that simulated epidemics on the network mimic a specified epidemic pattern. The evolutionary algorithm incorporates the novel recentering-restarting algorithm, which is adopted into the optimizer to allow for efficient search of the space of networks. It also implements the toggle-delete representation which allows for broader search of solution space. Then, a diffusion character based method is used for analyzing the contact networks. A comparison of simulated epidemics that result from changing patient zero for a single contact network is performed. It is found that the location of patient zero is important for the behaviour of an epidemic. The social fabric representation is invented and then tested for parameter choices. The response to vaccination strategies (including ring vaccination) is then tested by incorporating them into the epidemic simulations.en_US
dc.description.sponsorshipOntario Graduate Scholarship
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada
dc.identifier.urihttp://hdl.handle.net/10214/5266
dc.language.isoenen_US
dc.publisherUniversity of Guelphen_US
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectevolutionary computationen_US
dc.subjectepidemiologyen_US
dc.subjectcontact networksen_US
dc.subjectvaccinationen_US
dc.subjectpatient zeroen_US
dc.subjectdiffusion characteren_US
dc.subjectrecentering restartingen_US
dc.subjectsocial fabricen_US
dc.subjectring vaccinationen_US
dc.subjectnetwork topologyen_US
dc.subjectSIR modelen_US
dc.titleEvolving contact networks to analyze epidemic behaviour and studying the effects of vaccinationen_US
dc.typeThesisen_US

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