Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus

Description:

Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.

Creator(s): Corley, Courtney D.
Creation Date: May 2006
Partner(s):
UNT Libraries
Collection(s):
UNT Theses and Dissertations
Usage:
Total Uses: 213
Past 30 days: 4
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Creator (Author):
Publisher Info:
Publisher Name: University of North Texas
Place of Publication: Denton, Texas
Date(s):
  • Creation: May 2006
  • Digitized: April 11, 2008
Description:

Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.

Degree:
Level: Master's
Discipline: Computer Science
Language(s):
Subject(s):
Keyword(s): computational epidemiology | mathematical models | computer software | public health | vaccines | demographic impact
Contributor(s):
Partner:
UNT Libraries
Collection:
UNT Theses and Dissertations
Identifier:
  • OCLC: 70900930 |
  • ARK: ark:/67531/metadc5289
Resource Type: Thesis or Dissertation
Format: Text
Rights:
Access: Public
License: Copyright
Holder: Corley, Courtney D.
Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.