Research Article: Estimating the impact of antiretroviral treatment on adult mortality trends in South Africa: A mathematical modelling study

Date Published: December 12, 2017

Publisher: Public Library of Science

Author(s): Leigh F. Johnson, Margaret T. May, Rob E. Dorrington, Morna Cornell, Andrew Boulle, Matthias Egger, Mary-Ann Davies, Amitabh Bipin Suthar

Abstract: BackgroundSubstantial reductions in adult mortality have been observed in South Africa since the mid-2000s, but there has been no formal evaluation of how much of this decline is attributable to the scale-up of antiretroviral treatment (ART), as previous models have not been calibrated to vital registration data. We developed a deterministic mathematical model to simulate the mortality trends that would have been expected in the absence of ART, and with earlier introduction of ART.Methods and findingsModel estimates of mortality rates in ART patients were obtained from the International Epidemiology Databases to Evaluate AIDS–Southern Africa (IeDEA-SA) collaboration. The model was calibrated to HIV prevalence data (1997–2013) and mortality data from the South African vital registration system (1997–2014), using a Bayesian approach. In the 1985–2014 period, 2.70 million adult HIV-related deaths occurred in South Africa. Adult HIV deaths peaked at 231,000 per annum in 2006 and declined to 95,000 in 2014, a reduction of 74.7% (95% CI: 73.3%–76.1%) compared to the scenario without ART. However, HIV mortality in 2014 was estimated to be 69% (95% CI: 46%–97%) higher in 2014 (161,000) if the model was calibrated only to HIV prevalence data. In the 2000–2014 period, the South African ART programme is estimated to have reduced the cumulative number of HIV deaths in adults by 1.72 million (95% CI: 1.58 million–1.84 million) and to have saved 6.15 million life years in adults (95% CI: 5.52 million–6.69 million). This compares with a potential saving of 8.80 million (95% CI: 7.90 million–9.59 million) life years that might have been achieved if South Africa had moved swiftly to implement WHO guidelines (2004–2013) and had achieved high levels of ART uptake in HIV-diagnosed individuals from 2004 onwards. The model is limited by its reliance on all-cause mortality data, given the lack of reliable cause-of-death reporting, and also does not allow for changes over time in tuberculosis control programmes and ART effectiveness.ConclusionsART has had a dramatic impact on adult mortality in South Africa, but delays in the rollout of ART, especially in the early stages of the ART programme, have contributed to substantial loss of life. This is the first study to our knowledge to calibrate a model of ART impact to population-level recorded death data in Africa; models that are not calibrated to population-level death data may overestimate HIV-related mortality.

Partial Text: Substantial declines in adult all-cause mortality have been observed in South Africa since the mid-2000s [1–4], consistent with trends in other African countries [5–8]. Although these reductions are commonly attributed to the impact of antiretroviral treatment (ART) on HIV-related mortality, there has been no formal assessment of the extent to which the observed reduction in mortality is explained by the introduction of ART. A number of other factors could partly explain the reductions in mortality. First, adult HIV incidence in South Africa and other African countries peaked in the 1990s and has since declined substantially [9–11]. Some of the reduction in mortality may thus be due to the stage of the HIV epidemic. Second, HIV may be evolving towards a less virulent form [12,13]. Third, reductions in all-cause mortality could be a reflection of reductions in non-HIV mortality. By fitting mathematical models to mortality and HIV prevalence data, it is possible to evaluate which factors best explain the observed reductions in adult mortality.

The Thembisa model was used to simulate HIV transmission, disease progression, and mortality in South Africa. The model has previously been described [19], and S1 Text provides a more detailed explanation of the model parameters most relevant to the present analysis; the model is also freely available online (, Version 3.2 downloads). Briefly, the model is a deterministic model that divides the population into age- and sex-specific cohorts and ‘risk groups’ that are defined in terms of marital status and propensity for concurrent partnerships. Non-HIV mortality assumptions are based on an analysis of South African cause-of-death statistics [2]. The simulation of the HIV epidemic starts in 1985, based on an assumed initial prevalence of HIV in women in the high risk group. HIV incidence is simulated based on assumptions about rates of partnership formation, commercial sex activity, marriage, coital frequency, and condom use (all of which vary in relation to age and sex), as well as assumed probabilities of transmission per sex act. Probabilities of HIV transmission per act of unprotected sex depend on sex, relationship type, and the HIV stage of the HIV-positive partner. Transmission probabilities are assumed to be reduced after ART initiation, depending on assumed rates of viral suppression, and the female-to-male transmission probability is also assumed to be reduced if the male partner is circumcised.

HIV/AIDS has had a profound impact on adult mortality in South Africa, causing 2.7 million deaths in the 1985–2014 period. It is encouraging to see the dramatic impact that ART has had, saving 6.2 million adult life years in the period up to 2014, and reducing AIDS mortality in adults to only a quarter of what it would have been in the absence of ART. However, the slow pace of ART rollout, against a backdrop of political resistance to ART in the early 2000s [27], has had tragic consequences: our model estimates that the saving in life years could have been 2.7 million greater if the South African government had promoted ART more aggressively and adopted WHO guidelines in a more timely manner. These results are based on a model that has been calibrated to detailed and extensive HIV prevalence data, mortality data, HIV testing data, ART programme data, and estimates of mortality rates in ART research cohorts. Our model estimates that over 40% of adult HIV-related deaths in 2014 occurred in individuals who had been diagnosed but had not started ART. Our model also suggests that the observed mortality decline in South Africa over the last decade cannot be attributed only to the impact of ART, and changes in HIV virulence could also be partly responsible for the reduction.



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