Mathematical modeling for cost-effectiveness of pneumococcal vaccination strategies is being used to inform vaccine policy in a changing vaccine landscape.
Mathematical modeling is also being conducted to determine the impact of various strategies to prevent flu, including vaccine type and vaccine timing while the virus evolves, and new vaccines are developed.
Past modeling efforts with the Pittsburgh Supercomputing Center led to a 2017 Hyperion Innovation Excellence Award in High Performance Computing for agent-based modeling of influenza vaccine choice.