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dc.contributor.advisorGrenfellLevin, BryanSimon TA
dc.contributor.authorSaad-Roy, Chadi
dc.contributor.otherQuantitative Computational Biology Department
dc.description.abstractInfectious diseases exert substantial morbidity and mortality around the globe. Understanding the factors that shape the life histories and epidemiology of these diseases is thus crucial to determine appropriate control measures, inform policy, and aid vaccine development. Infectious diseases also provide powerful systems for exploring basic questions in cross-scale eco-evolutionary dynamics. In this thesis, I used theoretical models and computation to study multiple aspects of pathogen epidemiology and evolution, and the resulting effects on host population-level dynamics.In the first section of this thesis, I examine aspects of influenza eco-evolutionary dynamics. I begin with a synthesis of the progress on empirically-based theory for vaccine design and outlined future directions (Chapter 2). I then combine H1N1 sequence analyses with mutational robustness data to reconcile conflicting evidence on the evolutionary importance of electrostatic charge, thereby implicating local HA charge in evolutionary dynamics (Chapter 3). In the second section of this thesis, I use mathematical models of a pathogen with two infectious stages to study the evolution of an initial infectious stage that elicits no symptoms in hosts. First, I find that such a stage can emerge evolutionarily and be bistable with respect to a symptomatic stage (Chapter 4). Second, I show that the movement of individuals with fewer symptoms can impact evolutionary dynamics, such as leading to a decrease in the degree of symptoms in the first stage or to a qualitative change (Chapter 5). Lastly, I find that superinfection may induce new evolutionary behavior (Chapter 6). In the third section of this thesis, I examine how characteristics of host natural and vaccinal immunity shape SARS-CoV-2 dynamics. First, I derive analytical rela- tions for SARS-CoV-2 community immunity in settings with constant infection levels (Chapter 7). Second, I use simple population-level mathematical models to show how post-pandemic trajectories of SARS-CoV-2 crucially depend on the strength and duration of natural and vaccinal immunity (Chapter 8). Third, I investigate the epidemiological and evolutionary repercussions of SARS-CoV-2 vaccine dosing regimes (Chapter 9). Finally, I examine the potential consequences of ‘vaccine nationalism’ on SARS-CoV-2 dynamics (Chapter 10).
dc.publisherPrinceton, NJ : Princeton University
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=></a>
dc.subject.classificationApplied mathematics
dc.titleEco-evolutionary impacts on the dynamics and control of infectious diseases
dc.typeAcademic dissertations (Ph.D.)
pu.departmentQuantitative Computational Biology
Appears in Collections:Quantitative Computational Biology

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