SIS models and Network migration: a Framework for Dynamic models of Decision making under Infection

Abstract

This thesis studies the decision-making of a population as it changes under an epidemic spread in a closed geographic location. For this purpose we develop a hybrid dynamical system model that shows movement of the parts of the population (commuters) in the presence of a disease like influenza, and keeps track of the changes in the numbers of susceptible and infective individuals at each location. This model aims to monitor the effect of decision-making of the people moving on a daily basis between different cities that have attractive utilities, and how an epidemic may impact the travelling work force and primarily the local economy. This study shows how the choice of individuals (between missing work or going in sick, thus spreading the illness further) impacts the spread of disease and how it can be modeled to investigate the cost implied by these choices.