Applications of Mathematical Modelling to Infectious Disease Dynamics in Developing Countries.
Mathematical modeling has proven to be an essential tool for the development of
control strategies and in distinguishing driving factors in disease dynamics. A key
determinant of a given model's potential to aid in such measures is the availability
of data to parameterize and verify the model. For developing countries in particular,
data is often sparse and difficult to collect. It is therefore important to understand
the types of data that are necessary for a modeling project to be successful. In this
thesis I analyze the value of particular types of data for a set of infections. The first
project analyzes the importance of considering age-specific mixing patterns in vaccine
preventable infections in which disease severity varies with age. The second project
uses a simulated data set to explore the plausibility of recovering the parameters of an
epidemiological model from a time series data set of monthly dengue haemorrhagic
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