Modeling Emerging Infectious Diseases for Public Health Decision Support

dc.contributor.authorRivers, Caitlinen
dc.contributor.committeechairEubank, Stephen G.en
dc.contributor.committeechairLewis, Bryan L.en
dc.contributor.committeememberChretien, Jean-Paulen
dc.contributor.committeememberAlexander, Kathleen A.en
dc.contributor.departmentAnimal and Poultry Sciencesen
dc.date.accessioned2015-05-06T08:00:10Zen
dc.date.available2015-05-06T08:00:10Zen
dc.date.issued2015-05-05en
dc.description.abstractEmerging infectious diseases (EID) pose a serious threat to global public health. Computational epidemiology is a nascent subfield of public health that can provide insight into an outbreak in advance of traditional methodologies. Research in this dissertation will use fuse nontraditional, publicly available data sources with more traditional epidemiological data to build and parameterize models of emerging infectious diseases. These methods will be applied to avian influenza A (H7N9), Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV), and Ebola virus disease (EVD) outbreaks. This effort will provide quantitative, evidenced-based guidance for policymakers and public health responders to augment public health operations.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:4714en
dc.identifier.urihttp://hdl.handle.net/10919/52023en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectepidemiologyen
dc.subjectzoonosesen
dc.subjectemerging infectious diseasesen
dc.subjectinfectious disease modelingen
dc.titleModeling Emerging Infectious Diseases for Public Health Decision Supporten
dc.typeDissertationen
thesis.degree.disciplineGenetics, Bioinformatics, and Computational Biologyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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