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dc.contributor.advisorMwambi, Henry G.
dc.contributor.advisorZuma, Khangelani.
dc.creatorMzolo, Thembile.
dc.date.accessioned2010-08-18T07:28:24Z
dc.date.available2010-08-18T07:28:24Z
dc.date.created2009
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/10413/209
dc.descriptionThesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2009en_US
dc.description.abstractWhere HIV/AIDS has had its greatest adverse impact is on TB. People with TB that are infected with HIV are at increased risk of dying from TB than HIV. TB is the leading cause of death in HIV individuals in South Africa. HIV is the driving factor that increases the risk of progression from latent TB to active TB. In South Africa no coherent analysis of the risk determinants of HIV and TB has been done at the national level this study seeks to mend that gab. This study is about estimating risk determinants of HIV and TB. This will be done using the national household survey conducted by Human Sciences Research Council in 2005. Since individuals from the same household and enumerator area more likely to be more alike in terms of risk of disease or correlated among each other, the GEEs will be used to correct for this potential intraclass correlation. Disease occurrence and distribution is highly heterogeneous at the population, household and the individual level. In recognition of this fact we propose to model this heterogeneity at community level through GLMMs and Bayesian hierarchical modelling approaches with enumerator area indicating the community e ect. The results showed that HIV is driven by sex, age, race, education, health and condom use at sexual debut. Factors associated with TB are HIV status, sex, education, income and health. Factors that are common to both diseases are sex, education and health. The results showed that ignoring the intraclass correlation can results to biased estimates. Inference drawn from GLMMs and Bayesian approach provides some degree of con dence in the results. The positive correlation found at an enumerator area level for both HIV and TB indicates that interventions should be aimed at an area level rather than at the individual level.en_US
dc.language.isoenen_US
dc.subjectMathematical statistics.en_US
dc.subjectProbabilities.en_US
dc.subjectHIV infections--South Africa.en_US
dc.subjectAIDS (Disease)--Social aspects--South Africa.en_US
dc.subjectTuberculosis--Social aspects.en_US
dc.subjectAIDS (Disease)--Statistics.en_US
dc.titleEstimating risk determinants of HIV and TB in South Africa.en_US
dc.typeThesisen_US


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