Ph. D, Faculty of Science, University of Witwatersrand, 2011 / The evolution of drug resistance in human immunodeficiency virus (HIV) infection has
been a focus of research in many fields, as it continues to pose a problem to disease
prevention and HIV patient management. In addition to techniques of molecular
biology, studies in mathematical modelling have contributed to the knowledge here,
but many questions remain unanswered. This thesis explores the application of a
number of hybrid stochastic/deterministic models of viral replication to scenarios
where viral evolution may be clinically or epidemiologically important. The choice of
appropriate measures of viral evolution/diversity is non-trivial, and this impacts on
the choice of mathematical techniques deployed. The use of probability generating
functions to describe mutations occurring during early infection scenarios suggest
that very early interventions such as pre-exposure prophylaxis (PrEP) or vaccines
may substantially reduce viral diversity in cases of breakthrough infection. A modified
survival analysis coupled to a deterministic model of viral replication during transient
and chronic treatment helps identify clinically measurable indicators of the time it
takes for deleterious rare mutations to appear. Lastly, persistence of problematic
mutations is studied through the use of deterministic models with stochastic averaging
over initial conditions.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/10416 |
| Date | 14 September 2011 |
| Creators | Shiri, Tinevimbo |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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