Compartmental, Spatial, and Point Process Models for Infectious Diseases
Open Access
Author:
Goldstein, Joshua Randall
Graduate Program:
Statistics
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
September 22, 2015
Committee Members:
Murali Haran, Dissertation Advisor/Co-Advisor John Fricks, Committee Member Ephraim Mont Hanks, Committee Member Le Bao, Committee Member Matthew Joseph Ferrari, Committee Member
Keywords:
infectious disease models SIR models spatial point processes Gaussian processes Markov chain Monte Carlo
Abstract:
My dissertation research focuses on developing a range of methods for modelling infectious diseases. The classes of models I consider include (i) compartmental models, SIR models with a stochastic observation process, (ii) spatial gradient models, building upon a Gaussian process modeling framework, and (iii) Markov spatial point process models. In each case I am interested in understanding disease dynamics, either their spread or interactions. The scale of the dynamics I study varies from the cellular level (respiratory syncytial virus infections) to local populations in Africa (rotavirus infections) to county-level data in the U.S. (epidemics and invasive species). Computing challenges are a central part of this research, with a focus on Bayesian inference via Markov chain Monte Carlo.