Modeling Emerging Infectious Diseases for Public Health Decision Support

Emerging 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.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Genetics, Bioinformatics, and Computational Biology

Department dc:contributor.department

Animal and Poultry Sciences

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2015

Author dc:creator

• Rivers, Caitlin

Chairs dc:contributor.committeechair

• Eubank, Stephen G.
• Lewis, Bryan L.

Committee members dc:contributor.committeemember

• Chretien, Jean-Paul
• Alexander, Kathleen A.

• epidemiology
• zoonoses
• emerging infectious diseases
• infectious disease modeling

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:4714

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/52023