Modelling the demographic impact of HIV/AIDS in South Africa and the likely impact of interventions

This paper describes an approach to incorporating the impact of HIV/AIDS and the effects of HIV/AIDS prevention and treatment programmes into a cohort component projection model of the South African population. The modelled HIV-positive population is divided into clinical and treatment stages, and it is demonstrated that the age profile and morbidity profile of the HIV-positive population is changing significantly over time. HIV/AIDS is projected to have a substantial demographic impact in South Africa. Prevention programmes - social marketing, voluntary counselling and testing, prevention of mother-to-child transmission and improved treatment for sexually transmitted diseases - are unlikely to reduce AIDS mortality significantly in the short term. However, more immediate reductions in mortality can be achieved when antiretroviral treatment is introduced.antiretroviral treatment, demographic impact, HIV/AIDS prevention, simulation model, South Africa

The interaction between HIV and other sexually transmitted infections in South Africa: a model-based evaluation

Includes bibliographical references.Sexually transmitted infections (STIs) have been shown to increase the probability of HIV transmission, but there remains much uncertainty regarding the role of STI treatment in HIV prevention. This thesis aims to develop a mathematical model to estimate the prevalence of STIs in South Africa, the contribution of STIs to the spread of HIV, and the effects of changes in sexual behaviour and changes in STI treatment. A deterministic model is developed to simulate the transmission of HIV and six other STIs (syphilis, genital herpes, chancroid, gonorrhoea, chlamydial infection and trichomoniasis), as well as the incidence of bacterial vaginosis and vaginal candidiasis in women. The model is fitted to national HIV prevalence survey data, STI prevalence data from sentinel surveys and data from sexual behaviour surveys, using Bayesian techniques. Model results suggest that South Africa has some of the highest STI prevalence levels in the world, but that certain STIs – notably syphilis, chancroid, gonorrhoea and trichomoniasis – have declined in prevalence since the mid-1990s, following the introduction of syndromic management programmes and increases in condom use. STIs account for more than half of new HIV infections, and genital herpes is the most significant STI promoting the transmission of HIV. Syndromic management programmes reduced HIV incidence in South Africa by 3-10% over the decade following their introduction (1994-2004). Further reductions in HIV incidence could be achieved by promoting patient-initiated treatment of genital herpes, by addressing rising levels of drug resistance in gonococcal isolates, and by encouraging prompt health seeking for STIs. Concurrent partnerships are a major factor driving HIV transmission, accounting for 74-87% of new HIV infections over the 1990-2000 period. Halving unprotected sex in non-spousal relationships would reduce HIV incidence over the 2010 -2020 period by 32-43%. This thesis contributes to the understanding of HIV/AIDS epidemiology in South Africa by quantifying the contribution of various behavioural and biological factors to HIV transmission. This thesis also high lights several opportunities for reducing the future incidence of HIV. In addition, this thesis advances the assessment of uncertainty in STI models by proposing a Bayesian approach to incorporating sexual behaviour data and STI prevalence data into the parameter estimation proces

The relationship between intimate partner violence and HIV: A model-based evaluation

Background: Many studies have shown that women who have experienced intimate partner violence (IPV) are at a greater risk of HIV, but the factors accounting for this association are unclear, and trials of interventions to reduce IPV have not consistently reduced HIV incidence. Methods: This study uses an agent-based model, calibrated to South African data sources, to evaluate hypotheses about likely causal pathways linking IPV, HIV, and other confounding factors. Assumptions about associations between IPV and HIV risk behaviours were based on reviews of international literature. Findings: There is an association between past IPV experience and HIV incidence even when no causal effects are assumed (IRR 1.28, 95% CI 1.23e1.34), because women with a propensity for multiple partners are more likely to have ever been in a relationship with a violent partner. If, in addition, men with a propensity for concurrent relationships are more likely to perpetrate IPV, the IRR increases to 1.42 (95% CI 1.36e1.48), consistent with empirical IRR estimates. Alternative scenarios in which experience of IPV is assumed to cause changes in women's sexual behaviour have little effect on the IRR. An intervention that reduces IPV by 50% could be expected to reduce HIV incidence by at most 1.3%. Interpretation: Much of the observed association between IPV and HIV is likely to be due to confounding behavioural factors. Although interventions to reduce IPV are important, these interventions alone are unlikely to have a substantial impact on HIV incidence

Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa

Background: The UNAIDS targets for 2020 are to achieve a 90% rate of diagnosis in HIV-positive individuals, to provide antiretroviral treatment (ART) to 90% of HIV-diagnosed individuals and to achieve virological suppression in 90% of ART patients.Objectives: To assess South Africa’s progress towards the 2020 targets and variations in performance by province.Methods: A mathematical model was fitted to HIV data for each of South Africa’s provinces, and for the country as a whole. Numbers of HIV tests performed in each province were estimated from routine data over the 2002–2015 period, and numbers of patients receiving ART in each province were estimated by fitting models to reported public and private ART enrolment statistics.Results: By the middle of 2015, 85.5% (95% CI: 84.5% – 86.5%) of HIV-positive South African adults had been diagnosed, with little variation between provinces. However, only 56.9% (95% CI: 55.3% – 58.7%) of HIV-diagnosed adults were on ART, with this proportion varying between 50.8% in North West and 72.7% in Northern Cape. In addition, 78.4% of adults on ART were virally suppressed, with rates ranging from 69.7% in Limpopo to 85.9% in Western Cape. Overall, 3.39 million (95% CI: 3.26–3.52 million) South Africans were on ART by mid-2015, equivalent to 48.6% (95% CI: 46.0% – 51.2%) of the HIV-positive population. ART coverage varied between 43.0% in Gauteng and 63.0% in Northern Cape.Conclusion: Although South Africa is well on its way to reaching the 90% HIV diagnosis target, most provinces face challenges in reaching the remaining two 90% targets

HIV epidemic drivers in South Africa: A model-based evaluation of factors accounting for inter-provincial differences in HIV prevalence and incidence trends

Background: HIV prevalence differs substantially between South Africa’s provinces, but the factors accounting for this difference are poorly understood.Objectives: To estimate HIV prevalence and incidence trends by province, and to identify the epidemiological factors that account for most of the variation between provinces.Methods: A mathematical model of the South African HIV epidemic was applied to each of the nine provinces, allowing for provincial differences in demography, sexual behaviour, male circumcision, interventions and epidemic timing. The model was calibrated to HIV prevalence data from antenatal and household surveys using a Bayesian approach. Parameters estimated for each province were substituted into the national model to assess sensitivity to provincial variations.Results: HIV incidence in 15–49-year-olds peaked between 1997 and 2003 and has since declined steadily. By mid-2013, HIV prevalence in 15–49-year-olds varied between 9.4% (95% CI: 8.5%–10.2%) in Western Cape and 26.8% (95% CI: 25.8%–27.6%) in KwaZulu-Natal. When standardising parameters across provinces, this prevalence was sensitive to provincial differences in the prevalence of male circumcision (range 12.3%–21.4%) and the level of nonmarital sexual activity (range 9.5%–24.1%), but not to provincial differences in condom use (range 17.7%–21.2%), sexual mixing (range 15.9%–19.2%), marriage (range 18.2%–19.4%) or assumed HIV prevalence in 1985 (range 17.0%–19.1%).Conclusion: The provinces of South Africa differ in the timing and magnitude of their HIV epidemics. Most of the heterogeneity in HIV prevalence between South Africa’s provinces is attributable to differences in the prevalence of male circumcision and the frequency of nonmarital sexual activity

Community viral load and CD4 count distribution among people living with HIV in a South African Township: implications for treatment as prevention.

INTRODUCTION: The goals of scale-up of antiretroviral therapy (ART) have expanded from prevention of morbidity and death to include prevention of transmission. Morbidity and mortality risk are associated with CD4 count; transmission risk depends on plasma viral load (VL). This study aimed to describe CD4 count and VL distributions among HIV-infected individuals in a South African township to gain insights into the potential impact of ART scale-up on community HIV transmission risk. METHODS: A random sample of 10% of the adult population was invited to attend an HIV testing service. Study procedures included a questionnaire, HIV testing, CD4 count, and VL testing. RESULTS: One thousand one hundred forty-four (88.0%) of 1300 randomly selected individuals participated in the study. Two hundred sixty tested positive, giving an HIV prevalence of 22.7% [95% confidence interval (CI): 20.3 to 25.3]. A third of all HIV-infected individuals (33.5%, 95% CI: 27.8 to 39.6) reported taking ART. The median CD4 count was 417 cells per microliter (interquartile range, 285-627); 33 (12.7%, 95% CI: 8.9 to 17.4) had a CD4 count of ≤200 cells per microliter. VL measurements were available for 219 individuals (84.2%) and were undetectable in 72 (33.9%), >1500 copies per milliliter in 127 (58.0%) and >10,000 copies per milliliter in 96 (43.8%). Of those reporting they were receiving ART, 30.4% had a VL >1500 copies per milliliter compared with 58.0% of those reporting they were not receiving ART. CONCLUSIONS: A small proportion of those living with HIV in this community had a CD4 count of <200 cells per microliter; more than half had a VL high enough to be associated with considerable transmission risk. A substantial proportion of HIV-infected individuals remained at risk of transmitting HIV even after starting ART

Steady growth in antiretroviral treatment provision by disease management and community treatment programmes

Although access to highly active antiretroviral treatment (HAART) in the South African public health sector is closely monitored, much remains unknown regarding the numbers of HIV-positive individuals receiving HAART outside the public health sector. Access to HAART in the private health sector is probably considerably better than in the public health sector, as private sector patients can often afford the costs of HAART, and many are beneficiaries of medical schemes, which are required to provide HAART to eligible beneficiaries as a prescribed minimum benefit. An investigation conducted in 2005 found that by the middle of 2005, at least 50 000 South Africans were receiving HAART through disease management programmes (DMPs), workplace treatment programmes (all of which are administered by DMPs) or community treatment programmes. This investigation was repeated in 2006, with the objective of estimating the numbers of people receiving HAART by mid-2006 and the rate of growth in numbers on treatment between 2005 and 2006

Designing an optimal HIV programme for South Africa: Does the optimal package change when diminishing returns are considered?

Abstract Background South Africa has a large domestically funded HIV programme with highly saturated coverage levels for most prevention and treatment interventions. To further optimise its allocative efficiency, we designed a novel optimisation method and examined whether the optimal package of interventions changes when interaction and non-linear scale-up effects are incorporated into cost-effectiveness analysis. Methods The conventional league table method in cost-effectiveness analysis relies on the assumption of independence between interventions. We added methodology that allowed the simultaneous consideration of a large number of HIV interventions and their potentially diminishing marginal returns to scale. We analysed the incremental cost effectiveness ratio (ICER) of 16 HIV interventions based on a well-calibrated epidemiological model that accounted for interaction and non-linear scale-up effects, a custom cost model, and an optimisation routine that iteratively added the most cost-effective intervention onto a rolling baseline before evaluating all remaining options. We compared our results with those based on a league table. Results The rank order of interventions did not differ substantially between the two methods- in each, increasing condom availability and male medical circumcision were found to be most cost-effective, followed by anti-retroviral therapy at current guidelines. However, interventions were less cost-effective throughout when evaluated under the optimisation method, indicating substantial diminishing marginal returns, with ICERs being on average 437% higher under our optimisation routine. Conclusions Conventional league tables may exaggerate the cost-effectiveness of interventions when programmes are implemented at scale. Accounting for interaction and non-linear scale-up effects provides more realistic estimates in highly saturated real-world settings

Applied Remote Sensing Program (ARSP)

There are no author-identified significant results in this report

Eliminating Vertical Transmission of HIV in South Africa: Establishing a Baseline for the Global Alliance to End AIDS in Children

To gain a detailed overview of vertical transmission in South Africa, we describe insights from the triangulation of data sources used to monitor the national HIV program. HIV PCR results from the National Health Laboratory Service (NHLS) were analysed from the National Institute of Communicable Diseases (NICD) data warehouse to describe HIV testing coverage and positivity among children &lt;2 years old from 2017&ndash;2021. NICD data were compared and triangulated with the District Health Information System (DHIS) and the Thembisa 4.6 model. For 2021, Thembisa estimates a third of children living with HIV go undiagnosed, with NICD and DHIS data indicating low HIV testing coverage at 6 months (49%) and 18 months (33%) of age, respectively. As immunisation coverage is reported at 84% and 66% at these time points, better integration of HIV testing services within the Expanded Programme for Immunization is likely to yield improved case findings. Thembisa projects a gradual decrease in vertical transmission to 450 cases per 100,000 live births by 2030. Unless major advances and strengthening of maternal and child health services, including HIV prevention, diagnosis, and care, can be achieved, the goal to end AIDS in children by 2030 in South Africa is unlikely to be realised