Effective HIV prevention requires knowledge of the structure and dynamics of the social networks across which infections are transmitted. These networks are most commonly comprised of chains of sexual relationships. Whereas network data have long been collected during survey interviews, new data sources have become increasingly common in recent years. In this article, we review current and emerging methods for collecting HIV-related network data, as well as modelling frameworks commonly used to infer network parameters and map potential HIV transmission pathways within the network.
Botswana has made substantial progress towards meeting the UNAIDS 90-90-90 target by 2020 under which 90% of people living with HIV will know their status, 90% of these will be on anti-retroviral therapy (ART), and 90% of these will have viral loads below 400/µL. In this paper we use a previously published model for Botswana to assess the future impact of their HIV control programme on new HIV infections, AIDS related mortality and the costs of doing this. We show that while treatment will have a major impact on incidence and mortality and will lead to net cost savings, prevention will lead to further small reductions in incidence and mortality, but will entail significant cost increases.
Antiretroviral therapy (ART) markedly reduces the risk of sexual transmission of HIV. This inspired the idea of treatment as prevention (TasP) to reduce population HIV incidence, by reducing the infectiousness of HIV-infected individuals. However, increased infectiousness when treated individuals are co-infected with other sexually transmitted infections (STIs) could potentially undercut the effectiveness of TasP programs. As there is limited knowledge about the impact of STI co-infections on HIV shedding from individuals on ART, this study reviewed all published scientific evidence.
HIV testing is critically important to HIV prevention and treatment. Therefore UNAIDS has called for 90% of all HIV-positive individuals to be diagnosed by 2020. However, there are practical challenges associated with measuring progress towards this target. Many countries simply quote the proportion of adults who report having ever been tested for HIV in national household surveys. In a recent study, we attempted to obtain more accurate estimates of rates of HIV testing in South Africa, by combining survey data and routine testing data from health services. The results suggest that there is likely to be significant bias in self-reporting of past HIV testing. The results also show that South Africa has made substantial progress in scaling up access to HIV testing and counselling, with 76% of HIV-positive adults diagnosed by 2012. However, men and older adults appear to have a relatively low rate of HIV testing.
South Africa is the unenviable epicentre of the HIV pandemic with 0.7% of the global population sadly amassing 18% of the global prevalence. The government has expanded interventions over the years to quell the epidemic. Sadly however, 58% of South Africans eligible for ARV treatment remain unable to access it. Despite the strides made by government to alleviate the HIV burden, high HIV incidence rates of 16% were reported in 2013. We can gauge from this that the current prevention and treatment processes are failing. The question is: what alternatives do we have at our disposal? And could we gauge the potential success of these?
Concurrent partnerships have been suggested as a possible driver of the HIV epidemic in Southern Africa. To date, estimates of concurrency in published literature have been problematic due to poor definitions and measurement. We conducted a sexual behaviour survey in Cape Town that characterized concurrency by estimating the point prevalence, cumulative prevalence, incidence and degree distribution of concurrent partnerships. We also described the duration of overlaps for relationships begun in the previous year and the relative risk of having concurrent partnerships for different race and sex groups.
We would like to invite you to the Results Showcase for the Sexual Behavior Survey on Friday, 27 March, 2015 from 11am – 3pm at the Blue Hall in Khayelitsha.
In recent years, scientific innovations in HIV control have expanded the range of available interventions – male circumcision, topical microbicides, oral pre-exposure prophylaxis (PrEP) and treatment as prevention (TasP) have all sparked significant interest due to their potential effectiveness and versatility. While all these options are potentially available, resources remain limited and choosing which interventions to implement at scale is a difficult task, given the complex nature of disease transmission, the impact of behaviour in epidemic dynamics, and the different costs of these programs. Here we analyse the effects of scaling up PrEP and ART for HIV prevention in South Africa, to help decision makers understand how these interventions would work if considered independently or in combination.
Loss to follow-up (LTFU) is a serious problem in most sub-Saharan African ART programmes. If ART is interrupted or reduced, HIV again progresses, and this increases the risk of opportunistic infections and, ultimately, AIDS and death. In addition, the viral load of a patient who interrupts ART will rebound, and the probability of onward transmission increases. If tracing programmes can accelerate the return of lost patients, these patients may be less likely to transmit the virus, since the period of lapsed treatment is shortened. In this study, we created a mathematical model to determine whether tracing patients LTFU from ART programs would lower the rate of HIV transmission.
Young women in relationships with older men are typically at an elevated risk for acquisition of HIV in sub-Saharan Africa. Most qualitative studies have tended to focus on why women are motivated to participate in these relationships, offering little insight into perceived risks of these relationships. Therefore we conducted a qualitative study in three urban communities in Cape Town using thematic content analysis to explore women’s perceived risks of (non-)age-disparate relationships, the benefits of dating older men, and risk perceptions that influence decisions around these relationships.