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Thesis

Computational approaches to vaccine development for multi-strain pathogens

Abstract:

This thesis presents a number of computational approaches that I have used for the study, design, and optimization of vaccination strategy. An effective vaccination regimen against an infectious disease will elicit immune responses that target carefully selected regions of the parasite, and will be implemented in such a way that maximum benefit can be had. Here, I present research into various steps of the vaccine development pipeline, from developing new methods by which targets can be selected, to the best way that a therapy can be implemented in the field. Existing understanding of the ways in which populations of pathogens are structured is used to develop methods for selecting novel vaccination targets, that is, regions of pathogens against which a vaccine might be highly effective. These approaches are combined with mathematical modelling of vaccination at both within-host and population levels to assist in the development and implementation of vaccines against pathogens of global health importance. My within-host model suggests that a highly efficacious sterilely protective malaria vaccine may be possible by combining existing therapies. An epidemiological approach provides evidence that mass vaccination with a malaria vaccine of moderate efficacy, in combination with other interventions, may drive eradication in many transmission contexts. Considered together, the works contained within this thesis explore the ways in which both existing and novel therapies may be combined to gain maximum benefit.

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Division:
MPLS
Department:
Zoology
Role:
Author

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Role:
Supervisor
Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


UUID:
uuid:a9367868-01eb-4f2b-b3a2-c684957786a7
Deposit date:
2018-10-22
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