Date of Award

Fall 2012

Degree Type

Thesis

Degree Name

Master of Science (MSc)

Department

Applied Mathematics

Supervisor

David Earn

Co-Supervisor

Ben Bolker

Language

English

Committee Member

Jonathan Dushoff

Abstract

Infectious diseases spreading in a human population can occasionally exhibit sudden transitions in their qualitative dynamics. Previous work has been very successful in predicting such transitions in New York City's measles incidence rates using the standard SIR model (susceptible, infected, recovered). This work relied on a dataset spanning 45 years, which we have extended to 93 years (1891-1984). We continue previous research in transition analysis on this larger dataset, and compare resonant and transient periods predicted to exist in NYC's measles incidence rates with those observed through a continuous wavelet transform of the data. We find good agreement between SIR predictions and observation, and in particular note the likely existence of previously unobserved hysteresis early in our new time-series.

McMaster University Library


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