2. Academic Wits University Research Outputs (All submissions)

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    Two decades of mortality change in rural northeast South Africa
    (2014) Kabudula, C.W; Tollman, S; Mee, P
    Background: The MRC/Wits University Agincourt research centre, part of the INDEPTH Network, has documented mortality in a defined population in the rural northeast of South Africa for 20 years (1992 2011) using long-term health and socio-demographic surveillance. Detail on the unfolding, at times unpredicted, mortality pattern has been published. This experience is reviewed here and updated using more recent data. Objective: To present a review and summary of mortality patterns across all age-sex groups in the Agincourt sub-district population for the period 1992 2011 as a comprehensive basis for public health action. Design: Vital events in the Agincourt population have been updated in annual surveys undertaken since 1992. All deaths have been rigorously recorded and followed by verbal autopsy interviews. Responses to questions from these interviews have been processed retrospectively using the WHO 2012 verbal autopsy standard and the InterVA-4 model for assigning causes of death in a standardised manner. Results: Between 1992 and 2011, a total of 12,209 deaths were registered over 1,436,195 person-years of follow-up, giving a crude mortality rate of 8.5 per 1,000 person-years. During the 20-year period, the population experienced a major HIV epidemic, which resulted in more than doubling of overall mortality for an extended period. Recent years show signs of declining mortality, but levels remain above the 1992 baseline recorded using the surveillance system. Conclusions: The Agincourt population has experienced a major mortality shock over the past two decades from which it will take time to recover. The basic epidemic patterns are consistent with generalised mortality patterns observed in South Africa as a whole, but the detailed individual surveillance behind these analyses allows finer-grained analyses of specific causes, age-related risks, and trends over time. These demonstrate the complex, somewhat unpredicted course of mortality transition over the years since the dawn of South Africa’s democratic era in 1994.
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    A South African public- private partership HIV treatment model: viability and success factors
    (2014-10) Ingumbor J; Pascoe S; Rajap S; et al
    Introduction:The increasing number of people requiring HIV treatment in South Africa calls for efficient use of its human resources for health in order to ensure optimum treatment coverage and outcomes. This paper describes an innovative public-private partnership model which uses private sector doctors to treat public sector patients and ascertains the model's ability to maintain treatment outcomes over time. Methods: The study used a retrospective design based on the electronic records of patients who were down-referred from government hospitals to selected private general medical practitioners (GPs) between November 2005 and October 2012. In total, 2535 unique patient records from 40 GPs were reviewed. The survival functions for mortality and attrition were calculated. Cumulative incidence of mortality for different time cohorts (defined by year of treatment initiation) was also established. Results:The median number of patients per GP was 143 (IQR: 66-246). At the time of down-referral to private GPs, 13.8% of the patients had CD4 count <200 cell/mm3, this proportion reduced to 6.6% at 12 months and 4.1 % at 48 months. Similarly, 88.4% of the patients had suppressed viral load (defined as HIV-1 RNA <400 copies/ml) at 48 months. The patients' probability of survival at 12 and 48 months was 99.0% (95% Cl: 98.4%-99.3%) and 89.0% (95% Cl: 87.1%-90.0%) respectively. Patient retention at 48 months remained high at 94.3% (95% Cl: 93.0%-95.7%). Conclusions:T\ne study findings demonstrate the ability of the GPs to effectively maintain patient treatment outcomes and potentially contribute to HIV treatment scale-up with the relevant support mechanism. The model demonstrates how an assisted private sector based programme can be effectively and efficiently used to either target specific health concerns, key populations or serve as a stop-gap measure to meet urgent health needs.
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    Factors associated with mortality in HIV-infected people in rural and urban South Africa
    (2014) Otwombe, KN; Petzold, M; Modisenyane, T
    Background: Factors associated with mortality in HIV-infected people in sub-Saharan Africa are widely reported. However rural urban disparities and their association with all-cause mortality remain unclear. Furthermore, commonly used classical Cox regression ignores unmeasured variables and frailty. Objective: To incorporate frailty in assessing factors associated with mortality in HIV-infected people in rural and urban South Africa. Design: Using data from a prospective cohort following 6,690 HIV-infected participants from Soweto (urban) and Mpumalanga (rural) enrolled from 2003 to 2010; covariates of mortality were assessed by the integrated nested Laplace approximation method. Results: We enrolled 2,221 (33%) rural and 4,469 (67%) urban participants of whom 1,555 (70%) and 3,480 (78%) were females respectively. Median age (IQR) was 36.4 (31.0 44.1) in rural and 32.7 (28.2 38.1) in the urban participants. The mortality rate per 100 person-years was 11 (9.7 12.5) and 4 (3.6 4.5) in the rural and urban participants, respectively. Compared to those not on HAART, rural participants had a reduced risk of mortality if on HAART for 6 12 (HR: 0.20, 95% CI: 0.10 0.39) and 12 months (HR: 0.10, 95% CI: 0.05 0.18). Relative to those not on HAART, urban participants had a lower risk if on HAART 12 months (HR: 0.35, 95% CI: 0.27 0.46). The frailty variance was significant and 1 in rural participants indicating more heterogeneity. Similarly it was significant but B1 in the urban participants indicating less heterogeneity. Conclusion: The frailty model findings suggest an elevated risk of mortality in rural participants relative to the urban participants potentially due to unmeasured variables that could be biological, socio economic, or healthcare related. Use of robust methods that optimise data and account for unmeasured variables could be helpful in assessing the effect of unknown risk factors thus improving patient management and care in South Africa and elsewhere.
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