Modeling intervention strategies in epidemic disease outbreaks

Mathematical modeling is an essential tool in epidemiology. Models are constructed to describe the spread of an infectious disease in a population. This thesis focuses on deterministic compartmental models in which population is divided into distinct compartments depending on the state of infection of an individual throughout the course of an outbreak. The most basic model uses three compartments: Susceptible (S), Infected (I), and Recovered (R) as building blocks. We study improved SIR-type models involving more compartments to accommodate different states of infection, enabling response strategies to control the spread of a specific disease. Epidemics depend heavily on transmissibility of the disease, which can be measured by the basic reproduction number. We derive the basic reproduction number for each SIR-type model and use it to analyze the epidemic behavior. Response strategies to the spread of an infectious disease in a population often focus on containment and isolation of infected individuals as well as different types of vaccination programs. We use mathematical models and numerical simulations to predict the effect of vaccination and quarantine strategies on the spread of a disease in a homogeneous population. We conclude that a combination of intervention steps with highest priority on mass vaccination generate the best outcome in reducing and shortening the outbreak