This thesis investigates several uses of simulation methods to understand and control pandemic influenza in urban settings. An agent-based simulation, which models pandemic spread in a large metropolitan area, is used for two main purposes: to identify the shape of the distribution of pandemic outcomes, and to test for the presence of complex relationships between public health policy responses and underlying pandemic characteristics. The usefulness of pandemic simulation as a tool for assessing the cost-effectiveness of vaccination programs is critically evaluated through a rigorous comparison of three recent H1N1 vaccine cost-effectiveness studies. The potential for simulation methods to improve vaccine deployment is then demonstrated through a discrete-event simulation study of a mass immunization clinic.