Biomathematics

Singularly perturbed systems with or without delays commonly appear in mathematical modeling of physical and chemical processes, engineering applications, and increasingly, in mathematical biology. There has been intensive work for singularly
perturbed systems, yet most of the work so far focused on systems without
delays. In this thesis, we provide a new set of tools for the stability analysis for
singularly perturbed control systems with time delays.

Epidemic models help us predict the outcome of an epidemic. I will discuss and compare two simple epidemic models: a deterministic model implemented by a simple differential equation, and a stochastic model, which is more realistic, but harder to analyze. In both models we assume, for simplicity, that each individual goes through only two stages: healthy (susceptible) and sick (infective). Such models, called SI epidemic models, describe infections with no immunity. We will show that, when the population gets large, the more realistic stochastic model approaches the simple deterministic model on the average, which will allow us to see that the deterministic model is used for a good reason.