Modelling the dynamics of HIV related malignancies

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dc.contributor.advisorNyabadza, Faraien_ZA
dc.contributor.authorAkinlotan, Deborah Morenikejien_ZA
dc.contributor.otherStellenbosch University. Faculty of Science. Dept. of Mathematical Sciences.en_ZA
dc.date.accessioned2014-04-16T17:30:06Z
dc.date.available2014-04-16T17:30:06Z
dc.date.issued2014-04en_ZA
dc.descriptionThesis (MSc)--Stellenbosch University, 2014.en_ZA
dc.description.abstractENGLISH ABSTRACT: In recent years, HIV-associated cancers have proven to be the bane of our time, since HIV is decimating humanity across the globe, even in the twilight of the last century. Cancer rates continue to rise in developing countries, where 95% of the world’s HIV-infected population lives, yet less than 1% have access to antiretroviral therapy. HIV-infected individuals have a higher proclivity to develop cancers, mainly from immunosuppression. An understanding of the immunopathogenesis of HIV-related cancers (HRC) is therefore a major prerequisite for rationally developing and/or improving therapeutic strategies, developing immunotherapeutics and proplylatic vaccines. In this study, we explore the pathology of HIV-related cancer malignancies, taking into account the pathogenic mechanisms and their potential for improving the treatment of management of these malignancies especially in developing countries. We mathematically model the dynamics of malignant tumors in an HIV-free environment, investigate the impact of cancer malignancies on HIV-positive patients and explore the benefits of various therapeutic intervention strategies in the management of HIV-related cancers. We present two deterministic models of infectious diseases to implement these, and they were analysed. We use HIV-related lymphomas in the Western Cape of South Africa as a case study. We validated the proposed models using lymphoma incidence data from the Tygerberg Lymphoma Study Group (TLSG), Tygerberg Hospital, Western Cape, South Africa. We show that the increasing prevalence of HIV increases lymphoma cases, and thus, other HIV-related cancers. Our models also suggests that an increase in the roll-out of the HAART program can reduce the number of lymphoma cases in the nearest future, while it averts many deaths. Furthermore, the results indicate that a highly crucial factor to consider in the prognosis of the incidence of lymphoma (and other cancer types) in HIV-infected patients is their CD4 cell count, irrespective of whether the patient has developed an HRC or not.en_ZA
dc.format.extent131 p. : ill.
dc.identifier.urihttp://hdl.handle.net/10019.1/86573
dc.language.isoen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch University
dc.subjectTheses -- Mathematicsen_ZA
dc.subjectDissertations -- Mathematicsen_ZA
dc.subjectHIV infections -- Complicationsen_ZA
dc.subjectCanceren_ZA
dc.subjectLymphomasen_ZA
dc.subjectHIV infections -- Complications -- Mathematical modelsen_ZA
dc.subjectCancer -- Mathematical modelsen_ZA
dc.subjectLymphomas -- Mathematical modelsen_ZA
dc.subjectUCTDen_ZA
dc.titleModelling the dynamics of HIV related malignanciesen
dc.typeThesis
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