Browsing by Author "Musenge, Eustasius"
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Item Comorbidities in black South Africans with established rheumatoid arthritisLala, Vikash ; Mohammed, Tickly; Musenge, Eustasius ; Govind, NimmishaObjective: Comorbidities contribute both to morbidity and mortality in rheumatoid arthritis (RA). The aim of the current study was to investigate the prevalence and spectrum of comorbidities in South Africans with established RA. Methods: A retrospective, consecutive case record review of 500 Black South African patients with established disease of ≥5 years attending a tertiary rheumatology service was performed. Common comorbidities including those listed in the Charlson Comorbidity Score (CCS) were documented. Results: Most patients, 463 known alive (AG) and 37 known deceased (DG), were female (87%). Mean (SD) age and disease duration were 60 (11.1) and 10.7 (5.0) years respectively, and 98% had ≥1 comorbidities. Median CCS was 2, significantly higher in DG than AG (4 vs 2, P < .0001). Despite hypertension (70%) and hypercholesterolemia (47%) being the commonest comorbidities overall and type 2 diabetes (T2D) occurring in 15.4%, clinical cardiovascular events were rare (0.6%). Peptic ulcer disease (odds ratio [OR] = 8.67), congestive cardiac failure (OR = 7.09), serious infections (OR = 7.02) and tuberculosis (OR = 2.56) were significantly more common in DG than AG. Multivariate analysis showed that American College of Rheumatology functional class 3/4 was associated with increased risk for serious infections (OR = 3.84) and tuberculosis (OR = 2.10). Conclusion: Despite the high burden of cardiometabolic comorbidities in South Africans with established RA, cardiovascular events were rare. Serious infections and tuberculosis, both associated with severe functional disability, are a major cause of morbidity and mortality.Item Incidence estimation and calibration from cross-sectional data of acute infection HIV-1 seroconvertors(2009-03-16T08:29:07Z) Musenge, EustasiusABSTRACT Incidence estimation and calibration from cross-sectional data of acute infection HIV-1 seroconvertors. May 2007 Eustasius Musenge Masters in Medicine in the Field of Biostatistics and Epidemiology Supervised by: Mr E Marinda and Dr A Welte Background: The HIV-1 incidence (a very important measure used as a proxy for disease burden) can be estimated from a cross-sectional study. This incidence estimate has the advantage of reducing on costs and time, thus enabling more timely intervention; it is also ideal for developing nations. A common procedure used in making this estimate utilizes two antibody tests (Sensitive/Less sensitive tests). Due to the long window period of such tests (at least three months), persons classified as recently infected would have been infected more than three months prior to the test date. Detecting acute HIV-1 infection is very important since this is the most infectious stage of the disease. This research report explores a method of estimating incidence using an antibody test and a virological test, Polymerase Chain Reaction Ribonucleic Acid (PCR-RNA).The cross-sectional data used are from the Centre for the AIDS Programme of Research in South Africa (CAPRISA). Methods: Actual follow-up cohort data from CAPRISA acute infection cohort (AIC), comprised of 245 sex workers, were used to estimate the incidence of HIV-1 using a PCR-RNA ,virology test based, incidence formula. The result obtained was compared to the incidence estimate obtained by the classical method of estimating incidence the AIDS Programme of Research in South Africa (CAPRISA). Methods: Actual follow-up cohort data from CAPRISA acute infection cohort (AIC), comprised of 245 sex workers, were used to estimate the incidence of HIV-1 using a PCR-RNA ,virology test based, incidence formula. The result obtained was compared to the incidence estimate obtained by the classical method of estimating incidence (prospective cohort follow-up). As a measure to reduce costs inherent in virological tests (PCR-RNA), multistage pooling was discussed and several pooling strategies simulations were proposed with their uncertainties. Point estimates and interval estimates of the window period, window period prevalence and incidence from crosssectional study of the AIC cohort were computed. Findings: The mean window period was 6.6 days 95% CI: (2.7 – 13.0). The monthly window period prevalence was 0.09423 percent 95 % CI: (0.0193 – 0.1865)%. The incidence from the prospective cohort follow-up was 5.43 percent 95% CI: (3.9 – 9.2) %. The incidence estimate from cross-sectional formulae was 5.21 percent 95% CI: (4.1– 4.6). It was also shown by use of simulations that an optimum pool sample size is obtained when at least half the samples are removed on every run. Interpretation and recommendations: The PCR-RNA test is very sensitive at detecting acute HIV-1 infected persons. The incidence estimate from the crosssectional study formulae was very similar to that obtained from a follow-up study. The number of tests needed can be reduced and a good estimate of the incidence can still be obtained. The calibration was not accurate since the samples used were small and the window period duration was too short, hence, it was difficult to extrapolate to the whole population. Further work still needs to be done on the calibration of the proposed incidence formulae as it could be a very useful public health tool.Item Modelling spatiotemporal patterns of childhood HIV/TB related mortality and malnutrition: applications to Agincourt data in rural South Africa(2014-02-18) Musenge, EustasiusBackground: South Africa accounts for more than a seventh of the global population living with HIV/AIDS and TB, and ranks highest in HIV/TB co-infection worldwide. Consequent high child mortality is exacerbated by child malnutrition, which is an important indicator of health status and is associated with morbidity as well as mortality. Rural areas usually present with the greatest burden of morbidity and mortality, yet the extent of geographical disparities in child mortality, malnutrition and HIV/TB has hardly been explored. This is a reservoir of information useful for effective public health interventions. In this thesis we investigated the factors associated with childhood HIV/TB mortality and malnutrition, how they interrelate and their spatial distribution in the rural Agincourt sub-district located in north-east South Africa close to the border with Mozambique. Rationale: Africa at large lacks data that are routinely and reliably collected then validated, to guide policy and intervention programmes. Causes of deaths and even death counts are often misclassified and underestimated respectively, especially for children. To bridge this gap, a health and socio-demographic surveillance systems located in the rural Agincourt sub-district hosts which annually collects and collates data on vital events including fertility, mortality and migration. These data have been collected since 1992 to-date and now cover 80,000 people living in more than 16,000 households situated in 27 villages; all households are fully geo-coded. These hierarchical data allow us to address several epidemiological questions on how person, place (spatial) and time (temporality) have impacted on mortality and malnutrition patterns in children living in the rural Agincourt sub-district. Objectives: The aims of this thesis were both methodological and applied: Methodological (1) To investigate the presence of spatial autocorrelation in the Agincourt sub-district and model this using geographical and geo-statistical procedures (2) To model large spatial random effects accurately and efficiently (3) To model hierarchical data with zero inflated outcomes Applied (1) To investigate childhood HIV/TB mortality determinants and their geographical distribution using retrospective and cross-sectional data (2) To determine factors associated with malnutrition outcomes adjusting for their multivariate spatial random effects and selection bias for children under five years (3) To model how the associated factors were interrelated as either underlying or proximate factors of child mortality or malnutrition using pathway analysis. Methods: We conducted a secondary data analysis based on retrospective and cross-sectional data collected from 1992 to 2010 from the Agincourt sub-district in rural northeast South Africa. During the period of our study 71,057 children aged 0 to 9 years from 15,703 households were observed. All the data in the thesis were for children aged 1 to under 5 except for the chapter 6 (last paper) who were aged from 0 to 9 years of age. Child HIV/TB death and malnutrition were the outcome measures; mortality was derived from physicianbased verbal autopsy. We investigated presence of spatial autocorrelation using Moran’s and Geary’s coefficients, semi-variograms and estimated the spatial parameters using Bayesianbased univariate and multivariate procedures. Regression modelling that adjusted for spatial random effects was done using linear regression and zero inflated variants for logistic, Poisson and Negative Binomial regression models. Structural equation models were used in modelling the complex relationships between multiple exposures and child HIV/TB mortality and malnutrition portrayed by conceptual frameworks. Risk maps were drawn based on spatial residuals (posteriors) with prediction (kriging) procedures used to estimate for households where no data were observed. Statistical inference on parameter estimation was done using both the frequentist; maximum likelihood estimation and Bayesian; Markov Chain Monte Carlo (MCMC) directly and sometimes aided with Metropolis Hastings or Integrated Nested Laplace Approximations (INLA). Results: The levels of child under-nutrition in this area were: 6.6% wasted, 17.3% stunted and 9.9% underweight. Moran’s (I) and Geary’s (c) coefficients indicated that there was global and local clustering respectively. Estimated severity of spatial variation using the partial-sill-to-sill ratio yielded 12.1%, 4.7% and 16.5%, for weight-for-age, height-for-age and weight-for-height Z-scores measures respectively. Maternal death had the greatest negative impact on child HIV/TB mortality. Other determinants included being a male child and belonging to a household that had experienced multiple deaths. A protective effect was found in households with better socio-economic status and where older children were present. Pathway analyses of these factors showed that HIV had a significant mediator effect and the greatest worsening effect on malnutrition after controlling for low birth-weight selection bias Several spatial hot spots of mortality and malnutrition were observed, with these regions consistently emerging as areas of greater risk, which reinforces geographical differentials in these public health indicators. Conclusion: Modelling that adjusts for spatial random effects, is a potentially useful technique to disclose hidden patterns. These geographical differences are often ignored in epidemiological regression modelling resulting in reporting of biased estimates. Proximate and underlying determinants, notably socioeconomic status and maternal deaths, impacteddirectly and indirectly on child mortality and malnutrition. These factors are highly relevant locally and should be used to formulate interventions to reduce child mortality. Spatial prediction maps can guide policy on where to best target interventions. Child interventions can be more effective if there is a dual focus: treatment and care for those already HIV/TB infected, coupled with prevention in those geographical areas of greatest risk. Public health population-level interventions aimed at reducing child malnutrition are pivotal in lowering morbidity and mortality in remote areas. Keywords: HIV/TB, Child mortality, Child malnutrition, Conceptual framework, Spatial analysis, MCMC, Path analysis, South Africa