Kot, MarkStafford, Erin2024-02-122024-02-122024-02-122023Stafford_washington_0250E_26338.pdfhttp://hdl.handle.net/1773/51081Thesis (Ph.D.)--University of Washington, 2023Infectious-disease outbreaks in human, livestock, and plant populations continue to be a problem that can affect our day-to-day lives and have broader societal implications. There- fore, the need to prevent the spread of infectious disease is of great importance. Which disease-mitigation strategies are best depends on which factors are most important to decision makers. In this dissertation, I focus on the use of optimization with compartmental models to determine the best mitigation strategies for infectious-disease outbreaks. First, I describe the use of compartmental models to study infectious-disease dynamics. I also provide back- ground on optimal control theory and give examples of how optimal control theory and other optimization methods are used to give insight into the effectiveness of different disease mitigation strategies. Next, I use two optimal-control models to determine if contact-reducing disease-mitigation strategies can be economically advantageous when used to control the spread of Staphylococcus aureus in dairy cows. Both models use SIS models to describe the dynamics of S. aureus transmission. Moreover, both models consider revenue from healthy cows producing saleable milk, a cost from sick cows, and a loss of revenue when implementing mitigation strategies. The second model, however, also takes into consideration mild infections of S. aureus where infected cows may still produce saleable milk of lesser quality. Using these models, I found that using costly mitigation strategies to reduce contacts between infective and susceptible cows is economically beneficial. The dynamics of the second optimal-control model, where severity is considered, are more interesting as multiple candidate solutions satisfying the necessary conditions of Pontryagin’s maximum principle may coexist. The behaviors of these candidate solutions may be very different, but they may also produce similar economic outputs. I then study the effects of a very different type of disease-mitigation strategy, vaccination, on COVID-19 outcomes. In this chapter, I find which vaccination strategies minimize either overall disease burden, inequity in disease outcomes between racial groups, or a combination of measures. I find that, when vaccine is limited, there is a trade-off between minimizing disease burden and minimizing inequity. Allocation strategies that minimize combinations of measures can similarly improve both disease burden and inequity, but not to the same extent as when minimizing either measure alone. By increasing the vaccine supply, however, the trade-off greatly lessens.application/pdfen-USCC BYinfectious-disease modelingoptimal controloptimizationApplied mathematicsEpidemiologyPublic healthApplied mathematicsThesis