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Title: Estimation of Plasmodium falciparum allele and multi-SNP haplotype and genotype frequencies
Author: Taylor, Aimee Rebecca
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Malaria kills hundreds of thousands of people each year, yet is entirely curable given prompt treatment. Malaria parasites evolve resistance to antimalarial drugs, hence routine surveillance of antimalarial resistance is vital. The surveillance of parasite genetic markers of resistance provides an economical adjunct to clinical efficacy trials, and has the potential to resolve drug specific resistance ahead of clinical failure. To monitor spatiotemporal changes using genetic markers, frequencies of alleles and/or haplotypes and genotypes spanning multiple single nucleotide polymorphisms (SNPs) are required. However, multiclonal infections complicate frequency estimation, especially in highly endemic regions. With the aim of harnessing the full potential of genetic markers for the surveillance of antimalarial resistance, a statistical model to estimate frequencies is proposed. The model builds upon existing methods (reviewed in chapter 2), without reliance upon experimentally-derived estimates of the sample-wise multiplicities of infection (MOIs). Its ability to generate precise and accurate estimates within a Bayesian framework is documented in chapter 3. In chapter 4, the model is applied to data collected from a cohort of children enrolled in a longitudinal trial in Uganda, generating valuable insight into haplotype frequency trends. In chapter 5, the model is extended to investigate inter-child variability in the aforesaid cohort, revealing a small amount of inter-child variation. In chapter 6, the model is modified to enable the analysis of short-read sequencing data, with application to data from malaria patients in Northern Ghana, providing insight into the extent of within-host diversity and anti-folate resistance in the region. In summary, this thesis documents the development, application, extension and modification of a model designed to estimate population-level frequencies of P. falciparum alleles and multi-SNP haplotypes and genotypes within a Bayesian framework. It is hoped that the model and its proposed framework will provide a practical tool for surveillance of antimalarial resistance, as well as a foundation on which to develop further methods.
Supervisor: Holmes, Christopher ; Guérin, Philippe ; Flegg, Jennifer Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available