Analysis of partner turnover rate and the lifetime number of sexual partners in Cape Town using generalized linear models

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dc.contributor.advisorDelva, Wimen_ZA
dc.contributor.authorOlojede, Christianah Oyindamolaen_ZA
dc.contributor.otherStellenbosch University. Faculty of Science. Department of Mathematical Sciences.en_ZA
dc.date.accessioned2017-11-20T11:43:15Z
dc.date.accessioned2017-12-11T11:02:23Z
dc.date.available2017-11-20T11:43:15Z
dc.date.available2017-12-11T11:02:23Z
dc.date.issued2017-12
dc.descriptionThesis (MSc)--Stellenbosch University, 2017en_ZA
dc.description.abstractENGLISH ABSTRACT :A large number of analyses have been carried out to investigate how sexually active people contracted human immunodeficiency virus (HIV) by using common indicators like the number of new sexual partners in a given year and the lifetime number of partners. In this study, the objective is to show that these are not always good indicators because what people report for these two indicators is not accurate nor consistent using generalized linear models such as Poisson and the negative binomial regression models. Generalized linear models are the types of models that allows for the distribution of the response variable to be non-normal. A cross-sectional, sexual behavioural survey was conducted in communities with a high prevalence of HIV in Cape Town, South Africa, in 2011 – 2012. We examined the effects of age and gender on the rate at which sexual partnerships are formed, using count data regression models. The age range of respondents was 16-40 years. The highest number of new sexual relationships formed in a year preceding the survey was 11 and the highest lifetime number of sexual partners was 15. A generalized linear regression model was used to examine the consistency between the reported number of new sexual partners formed in a year preceding the survey and the reported lifetime number of partners. We also assessed the predictive power of these two indicators for the respondent’s HIV status. We found that these indicators are not consistent, and we conclude that they are not good indicators for predicting HIV status.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING : ‘n Hele aantal analises is reeds uitgevoer om ondersoek in te stel na hoe seksuele aktiewe persone menslike immuniteitsgebreksvirus (MIV) opdoen deur van die mees algemene indikators soos aantal nuwe seksuele metgeselle in ‘n gegewe jaar asook die aantal lewenslange seksuele verhoudings te gebruik. In hierdie navorsing, is die doel om aan te toon dat dit nie altyd die beste indikators is om te gebruik nie omdat persone nie konsekwent of akkuraat die werklike aantal nuwe seksuele verhoudings in ‘n jaar rapporteer nie deur veralgemeende lineêre model soos Poisson en negatief binomiaal regressie model le gebruik. ’n Veralgemeende lineêre model is die tipe model wat toelaat dat verspreiding van die responsveranderlike nie-normaal is. ‘n Dwarsdeursnit opname oor seksuele gedrag is uitgevoer in gemeenskappe met hoë prevalensie van MIV in Kaapstad, Suid Afrika tussen 2011 en 2012. Die effek van ouderdom en geslag wat die vormingskoers van nuwe seksuele verhoudings beïnvloed, is ondersoek met behulp van kategoriese (tellings of frekwensies) regressie-modelle. Die ouderdomme van die respondente het gewissel tussen 16 en 40 jaar. Die maksimum aantal nuwe seksuele verhoudings gevorm in ‘n jaar voor die opname was 11 en die maksimum aantal seksuele lewensmate waargeneem in die opname was 15. ‘n Veralgemeende lineêre regressie model is gebruik om die konsekwentheid tussen die gerapporteerde aantal nuwe seksulele verhoudings in die voorafgaande jaar van die opname met die gerapporteerde aantal lewenslange seksuele verhoudings te bepaal. Die voorspelde onderskeidingsvermoe van hierdie twee indikators vir MIV status is ook geassesseer. Daar is gevind dat hierdie indikators nie konsekwent is nie en gevolglik nie wenslik is om MIV status te voorspel nie.af_ZA
dc.format.extentxvi, 95, [5] pages : illustrations (some colour)en_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/102848
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subjectRegression models for count dataen_ZA
dc.subjectSexual partnersen_ZA
dc.subjectMathematical analysisen_ZA
dc.subjectGeneralized linear modelsaf_ZA
dc.subjectHIV infections -- Mathematical modelsen_ZA
dc.subjectHIV infections -- South Africa -- Cape Townen_ZA
dc.subjectRegression analysis -- Mathematical modelsen_ZA
dc.subjectUCTDen_ZA
dc.titleAnalysis of partner turnover rate and the lifetime number of sexual partners in Cape Town using generalized linear modelsen_ZA
dc.typeThesisen_ZA
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