Migration continues to play an important role in the spread of HIV-1 in South Africa. The direction of spread of the epidemic is not only from returning migrant men to their rural partners, but also from women to their migrant partners. Prevention efforts will need to target both migrant men and women who remain at home.

Migration is an independent risk factor for HIV infection among men. Workplace interventions are urgently needed to prevent further infections. High rates of HIV were found among rural women, and the migration status of the regular partner was not a major risk factor for HIV. Rural women lack access to appropriate prevention interventions, regardless of their partners' migration status.

BackgroundThree national HIV household surveys were conducted in South Africa, in 2002, 2005 and 2008. A novelty of the 2008 survey was the addition of serological testing to ascertain antiretroviral treatment (ART) use.Methods and Principal FindingsWe used a validated mathematical method to estimate the rate of new HIV infections (HIV incidence) in South Africa using nationally representative HIV prevalence data collected in 2002, 2005 and 2008. The observed HIV prevalence levels in 2008 were adjusted for the effect of antiretroviral treatment on survival. The estimated “excess” HIV prevalence due to ART in 2008 was highest among women 25 years and older and among men 30 years and older. In the period 2002–2005, the HIV incidence rate among men and women aged 15–49 years was estimated to be 2.0 new infections each year per 100 susceptible individuals (/100pyar) (uncertainty range: 1.2–3.0/100pyar). The highest incidence rate was among 15–24 year-old women, at 5.5/100pyar (4.5–6.5). In the period 2005–2008, incidence among men and women aged 15–49 was estimated to be 1.3/100 (0.6–2.5/100pyar), although the change from 2002–2005 was not statistically significant. However, the incidence rate among young women aged 15–24 declined by 60% in the same period, to 2.2/100pyar, and this change was statistically significant. There is evidence from the surveys of significant increases in condom use and awareness of HIV status, especially among youth.ConclusionsOur analysis demonstrates how serial measures of HIV prevalence obtained in population-based surveys can be used to estimate national HIV incidence rates. We also show the need to determine the impact of ART on observed HIV prevalence levels. The estimation of HIV incidence and ART exposure is crucial to disentangle the concurrent impact of prevention and treatment programs on HIV prevalence.

South Africa faces an epidemic of chronic non-communicable diseases (NCDs), yet national surveillance is limited due to the lack of recent data. We used data from the first comprehensive national survey on NCDs—the South African National Health and Nutrition Examination Survey (SANHANES-1 (2011–2012))—to evaluate the prevalence of and health system response to diabetes through a diabetes care cascade. We defined diabetes as a Hemoglobin A1c equal to or above 6.5% or currently on treatment for diabetes. We constructed a diabetes care cascade by categorizing the population with diabetes into those who were unscreened, screened but undiagnosed, diagnosed but untreated, treated but uncontrolled, and treated and controlled. We then used multivariable logistic regression models to explore factors associated with diagnosed and undiagnosed diabetes. The age-standardized prevalence of diabetes in South Africans aged 15+ was 10.1%. Prevalence rates were higher among the non-white population and among women. Among individuals with diabetes, a total of 45.4% were unscreened, 14.7% were screened but undiagnosed, 2.3% were diagnosed but untreated, 18.1% were treated but uncontrolled, and 19.4% were treated and controlled, suggesting that 80.6% of the diabetic population had unmet need for care. The diabetes care cascade revealed significant losses from lack of screening, between screening and diagnosis, and between treatment and control. These results point to significant unmet need for diabetes care in South Africa. Additionally, this analysis provides a benchmark for evaluating efforts to manage the rising burden of diabetes in South Africa.