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Applications of Nonlinear Systems of Ordinary Differential Equations and Volterra Integral Equations to Infectious Disease Epidemiology

Abstract In the field of infectious disease epidemiology, the assessment of model robustness outcomes plays a significant role in the identification, reformulation, and evaluation of preparedness strategies aimed at limiting the impact of catastrophic events (pandemics or the deliberate release of biological agents) or used in the management of disease prevention strategies, or employed in the identification and evaluation of control or mitigation measures. The research work in this dissertation focuses on: The comparison and assessment of the role of exponentially distributed waiting times versus the use of generalized non-exponential parametric distributed waiting times of infectious periods on the quantitative and qualitative outcomes generated b... (more)
Created Date 2014
Contributor Morale Butler, Emmanuel Jesús (Author) / Castillo-Chavez, Carlos (Advisor) / Aparicio, Juan P (Advisor) / Camacho, Erika T (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Subject Applied mathematics / Epidemiology / Statistics / Infectious Disease Epidemiology / Ordinary Differential Equations / Parameter Estimation or inverse problem / Stochastic modeling / Uncertainty and Sensitivity Analyses / Volterra Integral Equations
Type Doctoral Dissertation
Extent 171 pages
Language English
Reuse Permissions All Rights Reserved
Note Ph.D. Applied Mathematics for the Life and Social Sciences 2014
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis