In case of a pandemic influenza outbreak, non-pharmaceutical interventions will likely be the only containment measure at the early stages of the pandemic when vaccines are not available. NPIs also oer an option for decreasing the probability of creating antiviral resistant viruses product of a mass prophylaxis campaign. In countries where there are not enough resources for vaccines and antivirals, NPIs may be the only mitigation actions available. NPIs have been increasingly used in preparedness plans. We can see recommendations and guidelines regarding the use of NPIs in countries, health departments and universities. Also, researchers all around the world have study the impact of NPI's in pandemic influenza outbreaks, most of them using simulation as their modeling tool. Our review of the aforementioned plans and literature shows that there is a lack of consensus in how to implement these interventions. They vary widely in the choice of key parameters such as intervention initiation threshold, duration and compliance. We believe that the lack of uniformity in NPI mitigation strategies arise from the uncertainty in the virus epidemiology and the current lack of scientic knowledge about the complex interactions between virus epidemiology with social behavioral factors and mitigation actions. In this dissertation we addressed this problem by modeling pandemic influenza outbreaks using an agent-based simulation approach. The model incorporates detailed popu- lation demographics and dynamics, variety of mixing groups and their contact processes, infection transmission process, and non-pharmaceutical interventions. Using a statistical experimental design approach we examine the influence of characteristic parameters of virus epidemiology, social behavior, and non-pharmaceutical interventions on various measures of pandemic impact such as total number of infections, deaths and contacts. The experimental design approach also yields the knowledge of the extent of interactions among the above parameters. Using this knowledge we develop eective NPI strategies and demonstrate the efficacy of these strategies on large-scale simulated outbreaks involving three dierent scenarios of virus transmissibility. The results show that signicant improvements in the NPI based pandemic mitigation approaches can be attained by the strategies derived from our methodology.