Causing the deaths of millions of people annually, tuberculosis is now a universally shared threat. The emergence and spread of drug-resistant tuberculosis strains make effective treatment and control of tuberculosis complicated. Drug-resistance can arise from two sources: acquisition and transmission. Whole genome sequencing now plays an important role in bioinformatics and the research on infectious diseases. Based on the whole genome sequencing data of 110 tuberculosis isolates, a phylogenetic tree was built and the ancestral sequence was reconstructed. A simulation model was then designed to explore the development of drug-resistant tuberculosis in a population and resulted in about 300,000 tuberculosis patients. The tuberculosis patient clustering algorithm, which achieved desirable performance, was then proposed to cluster these tuberculosis patients into epidemiologically related groups. This research explored the transmission and acquisition of drug-resistant tuberculosis, and used modeling and algorithms in support of treatment and control of tuberculosis.
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Thesis advisor: Chindelevitch, Leonid
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