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Abstract
Human respiratory syncytial virus (RSV) is one of the leading causes of respiratory infections, especially in infants and young children. Despite the need to easily recognize RSV genotypes for molecular epidemiology, vaccine design, and control efforts, RSV classification criteria are not agreed upon and the potential association of RSV genotype with disease severity or immune response is almost unknown. In addition, RSV co-circulates with seasonal influenza in the U.S. every year causing significant epidemiological and economical burdens. However, very few studies have explored their potential interaction at the population level. To meet the vaccine and disease prevention needs of RSV and other respiratory pathogens, current global genomic data sharing, increased computing capability, and advanced molecular epidemiology methods have become powerful tools to understand rapidly evolving pathogens and have the potential to help us achieve the goal of effective prevention. In this dissertation, I describe the studies of RSV evolutionary and epidemiological dynamics of RSV using computational and statistical approaches to improve disease control. Chapter 2 of this dissertation focuses on developing a novel nomenclature system to better characterize the genetic diversity and evolution of RSV. In Chapter 3, I relate the observed RSV genetic diversity to potential T cell immune profiles. Using computational T cell epitope prediction approaches, we provide a T cell epitope landscape visualization that shows the co-circulation of three RSV-A T cell epitope groups and two RSV-B T-cell epitope groups, suggesting potentially distinct T cell immunity of different RSV circulating strains. In Chapter 4, we demonstrate RSV may have different evolutionary dynamics compared to seasonal influenza, in that local persistence that may play a role in underlying annual epidemics. We also provide evidence for the potential negative interaction of RSV and seasonal influenza at a population level. Taken together, the findings of this dissertation are important for understanding the evolution of RSV and can greatly enhance our ability to forecast future epidemics, vaccine design, and control strategy developments.