Doctoral Degrees (Epidemiology and Biostatistics)
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- ItemOptimisation and benchmarking of analytical approaches to estimation of population level HIV incidence from survey data(Stellenbosch : Stellenbosch University, 2022-04) Mhlanga, Laurette; Welte, Alex; Grebe, Eduard; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.ENGLISH SUMMARY: Disease prevalence (the proportion of a population with a condition of interest) is conceptually and procedurally much more straightforward to estimate than disease incidence (the rate of occurrence of new cases - for example, infections). For long-lasting conditions, incidence is fundamentally more difficult to estimate than prevalence, but also more interesting, as it sheds light on current epidemiological trends such as the emerging burden on health systems and the impact of recent policy interventions. Progress towards reducing reliance on questionable assumptions in the analysis of large population based surveys (for the estimation of HIV incidence) has been slow. The work of Kassanjee et al and the work of Mahiane et al, in particular, provide rigorous ways of estimating incidence by using 1) markers of ‘recent infection’, 2) the ‘gradient’ of prevalence, and 3) ‘excess mortality’ associated with HIV infection, without the need for simplifying assumptions to the effect that any particular parameters are constant over ranges of time and/or age. To date, the use of these methods has largely ignored 1) the rich details of the age and time structure of survey data, and 2) the opportunities for combining the two methods. The primary objective of this work was to find stable approaches to applying the Mahiane and Kassanjee methods to large age/time structured population survey data sets which include HIV status, and optionally, ‘recent infection’ status. In order to evaluate proposed methods, a sophisticated simulation platform was created to simulate HIV epidemics and generate survey data sets that are structured like real population survey data, with the underlying incidence, prevalence, and mortality explicitly known. The first non-trivial step in the analysis of survey data amounts essentially to performing a smoothing procedure from which the (age/time specific) prevalence of HIV infection, the prevalence of ‘recent infection’, and the gradient of prevalence of infection can be inferred without recourse to ‘epidemiological’ assumptions. The second step involves the correct accounting for uncertainty in a context-specific weighted mean of the Mahiane and Kassanjee estimators. These two steps are approached incrementally, as there are numerous details which have not previously been systematically elucidated. The investigation culminates in a proposed generic ‘once size fits most’ algorithm based on: 1) fitting survey data to generalised linear models defined by simple link functions and high order polynomials in age and time; 2) the use of a ‘moving window’ rule for data inclusion into a separate analysis for each age/time point for which incidence is to be estimated; 3) a ‘variance optimal’ weighting scheme for the combination of the Mahiane and Kassanjee estimators (when both are applicable); 4) flexible use of a delta method expansion or bootstrapping to estimate confidence intervals and p values. We find it is relatively easy to obtain estimates with practically negligible bias, but samplesizes/ sampling-density requirements are always considerable. We also make numerous observations on survey design and the inherent challenges faced by all attempts to estimate HIV incidence using surveys of reasonable size.
- ItemThe impact of missing data on estimating HIV/AIDS prevalence and incidence in demographic sentinel survey studies(Stellenbosch : Stellenbosch University, 2022-04) Mosha, Neema Ramadhani; Machekano, Rhoderick; Young, Taryn; Todd, Jim; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.ENGLISH SUMMARY: Background: Missing data is a challenge in most research, especially with observational population data such as demographic surveys. These studies often account for survey designs and clustering when estimating disease prevalence or incidence, but do not account for missing data. In other circumstances they do not explicitly state how they dealt with missing data during analysis or inappropriately handles them in practice. There are many challenges in conceptualising the pattern of missingness, its occurrence mechanism and complexity of methods for handling the problem of missing data. Ignoring the missingness of survey data can cause biased estimates and invalid conclusions. The primary aim of this PhD was to evaluate the impact of missing data on estimating HIV/AIDS prevalence in demographic sentinel surveillance studies. Methods: A systematic review of HIV studies to identify and describe methods used to analyse studies with missing data was done. A series of simulation studies to explore the precision and efficiency of the prevalence estimates using complete case analysis (CCA), multiple imputation (MI), inverse probability weighting (IPW) and double robust estimator (DR), when data are missing at random (MAR) in survey studies was done. A descriptive statistics and a complete case analysis to determine the incidence and population prevalence estimates ignoring the missingness on four different survey rounds of Magu Health Demographic Sentinel Surveillance (HDSS) was done.The surveys were conducted between 2006 and 2016, they included adults aged 15 years and above and about 50% of the population was tested for HIV in each survey. This was followed by data exploration assessing the missingness occurrence and association between missingness and other study characteristics. Finally, application of the statistical methods used in the simulations study was performed to re-estimate the prevalence of the surveys data taking into account the missingness. Results: The systematic review found 24 eligible articles from population, demographic and cross-sectional surveys that acknowledged the presence of missing data. In these studies, complete case analysis was the standard method of choice (100%) followed by multiple imputations (46%) and Heckman’s selection models (38%). A simulation study generated a hypothetical HIV survey with 32 different scenarios exploring data when an outcome is missing 20% and 55%. This simulation showed that when data are MAR, complete case analysis produces biased and inefficient estimates. Results showed that the three methods (MI, IPW and DR) were valid and efficient if the missingness or imputation models are correctly specified, but if either of the MI or IPW models are mis-specified, then the DR estimator can still be valid. Regarding to performance of the methods, provided that correct models are used, MI is more unbiased even when there is 55% of the data missing. However with 55% missingness all estimators are less reliable. In the complete case analysis, the overall population prevalence estimates for HIV decreased from 7.2% in 2006 to 6.6% in 2016. Cox models were used to determine HIV incidence rates and risk factor analysis by sex. The incidence rate was 5.5 per 1000 person - years in women compared to 4.6 per 1000 person-years in men. Residence, marital status, mobile individuals, and individuals with two or more partners were associated with the increase in incidence of HIV in bivariate analysis. The missingness OF HIV was as high as 60.3% (in the 2016 survey) and in all surveys(Sero 5 to 8) it was associated with age, sex, residence, and marital status. Further analysis using MI, IPW and DR assuming the outcome was MAR showed that the overall HIV prevalence was not significantly different from the complete case analysis in all four of the surveys. However, there were significant differences in the HIV estimates when stratified by the covariates. Looking at the confidence intervals width multiple imputations outperformed IPW and DR by producing more narrower estimates. Conclusion: Overall, this dissertation showed that despite the availability of methods to adjust for missing data, many surveys still ignore the missingness. The reporting among articles adjusted for missingness was below guideline standards. Understanding the mechanism of missingness enhances the proper application of advanced methods to account for the missingness. With data missing at random, IPW, MI, and DR can account for the missingness and produce unbiased and efficient estimates in HIV survey studies. Also, more simplified information and awareness are still needed to allow researchers to make informed choices, specifically on which method to apply and in which situation it works best for the estimates to be more reliable and representative.
- ItemAssessment of point-of-care testing for prediction of aromatase inhibitor-associated side effects in obese postmenopausal breast cancer patients screened for cardiovascular risk factors(Stellenbosch : Stellenbosch University, 2021-12) Milambo, Jean Paul Muambangu; Akudugu, John M.; Nyasulu, Peter S.; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.ENGLISH SUMMARY : Background: Aromatase inhibitors (AIs) constitute a standard of care for post- and premenopausal patients with estrogen receptor-positive breast cancer (BC). Obesity and mediators of inflammation have been identified as the most important risk and predictive factors in postmenopausal breast cancer survivors (BCS) using AIs. However, data on the feasibility of point-of-care (POC) genotyping using high sensitivity C-reactive protein (hs-CRP) and body mass index (BMI) as predictors of drug toxicity among postmenopausal BCS in African clinical settings are lacking. Aim: The study was conducted to assess the impact of AIs on hs-CRP and BMI, which are used at POC for prediction of therapy-associated side effects among obese postmenopausal breast cancer patients in Africa. Methods: One hundred and twenty-six female BC patients with cancer stages ranging from 0-III were recruited at Tygerberg Hospital (TBH) in the Western Cape Province of South Africa, between August 2014 and February 2017, for the study. A Quasi-experimental study was conducted. Patients were initially subjected to AIs and subsequently followed up at months 4, 12, and 24. Baseline clinical and biomedical assessments were conducted at commencement of study to predict hs-CRP and BMI at months 12 and 24, using a multiple imputation model. A random effects model was used to monitor the changes over the time. Statistical analyses were performed using SPSS 18.0 software (SPSS Inc., Chicago, IL, USA) and STATA version 16. Analyses were two-tailed and a p-value < 0.05 was considered statistically significant. Results: The mean age of the participants was 61 years (SD = 7.11 years; 95% CI: 60-62 years). Linear regression revealed that hs-CRP was associated with waist circumference (OR: 7.5; p= 0. 0116; 95%CI: 1.45 to 39.61) and BMI (OR: 2.15; p=0.034, 95%CI: 1.02 to 4.56). Waist circumference was associated with hypertension (OR: 3, 83; p= 0.003, 95%CI: 1.56 to 9.39), and chemotherapy was associated with waist circumference by (p= 0. 016; 95%CI: 0.11 to 0. 79). hs-CRP levels were significantly correlated with BMI and total body fat (TBF) among postmenopausal using aromatase inhibitors. Random linear effects modelling revealed stronger statistical association between BMI and homocysteine (p=0.021, 95%CI: 0.0083 to 0.1029). Weight and TBF were strongly associated after 24 months of follow-up. In addition, hs-CRP was associated with BMI (p=0.0001) and other inflammatory markers such as calcium (p=0.021, 95%CI: 0.0083 to 0.1029), phosphate (p=0.039, 95%CI: 0.0083 to 0.1029), and ferritin (p=0.002, 95%CI: 0.0199 to 0.084). Multiple imputation modelling indicated that there were statistically significant variations in TBF, weight, homocysteine, ferritin, and calcium between baseline and after 24 months of follow-up. Mathematical modeling Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that yielded sensitivity of 99% (95% CI: 94.55 to 99.97%), specificity of 89.44% (95% CI: 87.25 to 91.38%), PPV of 51% (95%: 43.77 to 58.26%), and NPV of 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that incremental cost-effective ratio (ICER) was R7 044.55. Conclusion: This study revealed that hs-CRP and BMI are predictors of CVD-related adverse events in obese postmenopausal patients. Calcium, phosphate, homocysteine, and ferritin should also be incorporated in POCT. There were statistically significant variations in TBF, weight, hs-CRP, BMI, homocysteine, ferritin, and calcium between baseline and after 24 months of follow-up. HyBeacon® probe technology at POC for AI-associated adverse events maybe cost-effective in Africa while adjunct to standard practice. The appropriate pathways for implementation of POC testing in postmenopausal breast cancer survivors need further investigation in different clinical settings with real data for external validation.
- ItemBurden of congenital rubella syndrome and potential impact of rubella vaccine introduction in South Africa(Stellenbosch : Stellenbosch University, 2021-12) Motaze, Nkengafac Villyen; Wiysonge, Charles S.; Suchard, Melinda S.; Metcalf, C. Jessica E.; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.ENGLISH SUMMARY : Background: Introduction of rubella vaccines into public vaccination schedules of all countries is necessary if global rubella elimination is to be achieved. Rubella is targeted for elimination in five World Health Organization (WHO) regions and several international organizations, under the stewardship of the WHO, are working towards this goal. Although there is no rubella elimination or control target for the WHO Africa region, there has been accelerated introduction of rubella vaccination on the continent. South African government is planning to introduce rubella vaccination in its Expanded Programme on Immunization (EPI) schedule and several epidemiological studies have been conducted to aid preparation of this public health intervention. In the absence of vaccination, rubella is mainly a mild endemic childhood viral illness that is asymptomatic in up to 50% of cases. The most severe consequences of rubella occur when infection occurs during pregnancy. These include miscarriages, stillbirths, intra-uterine growth restriction and congenital rubella syndrome. Rubella vaccines are therefore intended to prevent rubella and associated complications. In South Africa, rubella vaccines are not part of the EPI schedule and there is limited information on the epidemiology of rubella and its complications. In addition, the South African government has to cover the cost of introducing rubella vaccination. Therefore, the aim of this research project was to characterize the epidemiology of rubella and congenital rubella syndrome in South Africa, to assess the potential impact of introducing rubella vaccination in the EPI schedule. Methods: Four different studies were carried out as part of this PhD project: a cross-sectional descriptive study, a sero-survey, a mathematical modelling study and a systematic review. Results: The findings of a newly established CRS surveillance system to provide data on disease trends in the absence of rubella vaccination are presented in the first research component. We provided baseline data on laboratory-confirmed CRS that will enable planning and monitoring of RCV implementation in the South African EPI program. Ninety-eight percent of mothers of infants with CRS were young women 14 to 30 years old, indicating a potential immunity gap in this age group for consideration during introduction of RCV. In the second research component, we present results of testing on residual samples collected from public health facilities to identify immunity gaps in various age groups and genders. The bulk of individuals susceptible to rubella are children under sixteen years old and about 20% of individuals 16 to 49 years old are susceptible to rubella. In multivariable logistic regression, age and province of residence were found to be associated with rubella susceptibility.Webuilt on a previously published mathematical model adapted to the South African context in the third research component and provide insights into optimal scenarios for RCV introduction into the South African public immunization schedule. We simulated a number of scenarios that combined infant vaccination with vaccination of older individuals. Routine vaccination at 12 months of age coupled with vaccination of nine-year-old children was associated with the lowest RCV cost per CRS case averted for a similar percentage CRS reduction. Interestingly, at 80% RCV coverage, all vaccine introduction scenarios could achieve rubella and CRS elimination in South Africa.In the final research component, we systematically reviewed mathematical modelling studies to identify the most effective approach for countries introducing RCV into their public immunization schedules. There were variations in the manner in which individual studies reported outcomes. However, we found that better outcomes are obtained when rubella vaccination is introduced into public vaccination schedules at coverage figures of 80%, as recommended by WHO, or higher. Conclusion: The results from these different studies support the implementation of a strategy involving infant vaccination in combination with vaccination of older individuals. Further research projects are required to provide more detail on the burden of CRS and the economic impact of RCV introduction into the EPI schedule.
- ItemAn evaluation of the effectiveness of task-shifting health systems approaches, including community-based and pharmaceutical care models, for HIV treatment and prevention programs in South Africa(Stellenbosch : Stellenbosch University, 2020-12) Fatti, Geoffrey; Chikte, Usuf M. E.; Nachega, Jean; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Global Health. Epidemiology and Biostatistics.ENGLISH SUMMARY : Southern Africa is the epicenter of the human immunodeficiency virus (HIV) pandemic having the highest burden of HIV globally. Although South Africa has made great strides with the roll-out of its antiretroviral treatment (ART) program, ongoing challenges include high attrition of patients from ART care and ongoing elevated HIV incidence. There is also a severe shortage of professional health workers in the region, which impacts HIV program delivery. Task-shifting health systems approaches have been developed in order for the health system to provide large-scale HIV program delivery with limited numbers of professional health workers. This thesis evaluates the effectiveness of task-shifting health systems interventions in HIV prevention and treatment programs in South Africa, including community-based programs utilizing community healthcare workers (CHWs), and pharmaceutical care models. Data were collected in cohort studies conducted between 2004 and 2015/2016 in four provinces of South Africa. The results chapters of the thesis are presented in the form of published papers. The first paper evaluates the effectiveness of a community-based support (CBS) program amongst a large cohort of adults living with HIV receiving ART up to five years after ART initiation. Adults who received CBS had improved ART outcomes, including improved patient retention with lower loss to follow-up and lower mortality, both of which were reduced by one third. The second paper evaluates the effectiveness of a community-based combination HIV prevention intervention delivered by CHWs for pregnant and postpartum women in a high HIV incidence district in KwaZulu-Natal. Maternal HIV incidence amongst participants who received the intervention was considerably lower compared to other studies from the region. The paper further recommends expanded roll-out of home-based couples HIV counselling and testing, and initiating oral pre-exposure prophylaxis for HIV particularly for pregnant women within serodiscordant couples, in order to reduce maternal HIV incidence. The third paper compares the effectiveness and cost of two task-shifting pharmaceutical care models for ART delivery in South Africa, namely the indirectly supervised pharmacist assistant (ISPA) model and the nurse-managed model. The ISPA model was found to have a higher quality of pharmaceutical care, was less costly to implement and was possibly associated with improved patient clinical outcomes. The fourth paper evaluates the effectiveness and cost-effectiveness of CBS for adolescents and youth receiving ART at 47 health facilities in South Africa. CBS was found to substantially reduce patient attrition from ART care in adolescents and youth, and was a low cost intervention with reasonable cost-effectiveness. Lastly, a published scientific letter is included as an appendix, which is a critique of findings from a cluster-randomized trial investigating the effectiveness of two interventions as part of the current South African National Adherence guidelines (AGL). The letter recommends the inclusion of long-term CBS for ART patients utilizing CHWs in a revised version of the AGL. The thesis concludes that task-shifting healthcare models including communitybased and pharmaceutical care models are effective and cost-efficient for HIV program delivery in South Africa, and can aid the greater Southern African regions’ progress toward several of the interrelated UNAIDS Sustainable Development Goals by 2030.