ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at firstname.lastname@example.org.
- 2 Public
- 1 AH1N1
- 1 Applied mathematics
- 1 Biology
- 1 Infectious Disease Epidemiology
- 1 Influenza
- 1 Markov Chains
- 1 Mathematics
- 1 Metapopulation
- 1 Ordinary Differential Equations
- 1 Parameter Estimation or inverse problem
- 1 Statistics
- 1 Stochastic Processes
- 1 Stochastic modeling
- 1 Uncertainty and Sensitivity Analyses
- 1 Vaccination
- 1 Volterra Integral Equations
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 …
- Morale Butler, Emmanuel Jesús, Castillo-Chavez, Carlos, Aparicio, Juan P, et al.
- Created Date
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that …
- Cruz-Aponte, Maytee, Wirkus, Stephen A., Castillo-Chavez, Carlos, et al.
- Created Date