Description:
We present approaches utilizing aspects of data analytics and stochastic modeling techniques and applied to various areas in healthcare. In general, the thesis has composed of three major components. Firtsly, we propose a comparison analysis between two of the very well-known infectious disease modeling techniques to derive effective vaccine allocation strategies. This study, has emerged from the fact that individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about the possible differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models. Secondly, we introduce a novel and holistic scheme to capture the gradual amyotrophic lateral sclerosis progression based on the critical events referred as tollgates. Amyotrophic lateral sclerosis is neuro-degenerative and terminal ...
Publisher:
University of Waterloo
Year of Publication:
2017-12-14
Document Type:
Doctoral Thesis ; [Doctoral and postdoctoral thesis]
Language:
en
Subjects:
Healthcare ; Optimization ; Stochastic modeling ; data analytics ; medical decision making ; Influenza ; Amyotrophic lateral sclerosis
Content Provider:
University of Waterloo, Canada: Institutional Repository  Flag of Canada