Modeling Infectious Disease Spread Using Global Stochastic Field Simulation Metadata

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Title

  • Main Title Modeling Infectious Disease Spread Using Global Stochastic Field Simulation

Creator

  • Author: Venkatachalam, Sangeeta
    Creator Type: Personal

Contributor

  • Chair: Mikler, Armin R.
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Jacob, Roy T.
    Contributor Type: Personal
  • Committee Member: Oppong, Joseph R.
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas

Date

  • Creation: 2006-08
  • Digitized: 2008-04-02

Language

  • English

Description

  • Content Description: Susceptibles-infectives-removals (SIR) and its derivatives are the classic mathematical models for the study of infectious diseases in epidemiology. In order to model and simulate epidemics of an infectious disease, a global stochastic field simulation paradigm (GSFS) is proposed, which incorporates geographic and demographic based interactions. The interaction measure between regions is a function of population density and geographical distance, and has been extended to include demographic and migratory constraints. The progression of diseases using GSFS is analyzed, and similar behavior to the SIR model is exhibited by GSFS, using the geographic information systems (GIS) gravity model for interactions. The limitations of the SIR and similar models of homogeneous population with uniform mixing are addressed by the GSFS model. The GSFS model is oriented to heterogeneous population, and can incorporate interactions based on geography, demography, environment and migration patterns. The progression of diseases can be modeled at higher levels of fidelity using the GSFS model, and facilitates optimal deployment of public health resources for prevention, control and surveillance of infectious diseases.

Subject

  • Library of Congress Subject Headings: Epidemiology -- Mathematical models.
  • Keyword: computational epidemiology
  • Keyword: simulation
  • Keyword: modeling

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights License: copyright
  • Rights Holder: Venkatachalam, Sangeeta
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • OCLC: 75183344
  • Archival Resource Key: ark:/67531/metadc5335

Degree

  • Degree Name: Master of Science
  • Degree Level: Master's
  • Degree Discipline: Computer Science
  • Academic Department: Department of Computer Science and Engineering
  • Degree Grantor: University of North Texas

Note

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