Date of Award
5-2011
Document Type
Thesis
Degree Name
Master of Science (MS)
College/School
College of Science and Mathematics
Department/Program
Mathematical Sciences
Thesis Sponsor/Dissertation Chair/Project Chair
Lora Billings
Committee Member
Diana Thomas
Committee Member
Eric Forgoston
Abstract
Researchers using mathematical models have made significant contributions to the field of epidemiology in recent years. These models have both explanatory and predicative power to describe disease dynamics. More recent work has considered multi-population models and the effects vaccinations have on the population as a whole. One such example can be seen in the West African country of Cameroon, which has two distinct patterns of measles outbreaks. By considering Cameroon as two subpopulations, a deterministic model is developed that includes the effect of vaccinations. Stability analysis is then performed on the model over a range of coupling and vaccination rates to establish thresholds between disease absence and persistence. Stochastic methods are then used to capture low probability events near these thresholds. We identified significant differences in vaccination rates predicted deterministically for disease absence versus vaccination rates that are effective at inducing disease absence.
File Format
Recommended Citation
Burton, Jackson, "Capturing Low Probability of Disease Dynamics in Coupled Populations" (2011). Theses, Dissertations and Culminating Projects. 787.
https://digitalcommons.montclair.edu/etd/787