Intimate partner violence (IPV) is a worldwide epidemic. Physical and sexual violence are the most well-studied forms of IPV from an epidemiological point of view. Both of these have serious implications for other aspects of physical and mental health. In particular, women who have experienced IPV are more likely to be HIV-positive. In a modelling study we investigated some closely related questions about HIV and IPV in South Africa.
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.
The history of tenofovir exemplifies the success of international procurement agencies in securing a rock bottom price while at the same time making a profit.
The current issue of the SACEMA Quarterly focuses on research findings on South Africa that have been presented at the 19th Conference on Retroviruses and Opportunistic Infections (CROI) that was held from 5-8 March 2012 in Seattle. The role of treatment as prevention and combining different strategies to reduce the HIV incidence continue to be hot topics. The study by Ramzi Alsallaq et al. focuses on mathematical modelling on the impact of combined interventions on the short- and long-term incidence of HIV in KwaZulu-Natal. As this is just one of the large number of mathematical models predicting the incidence of HIV in South Africa, the HIV Modelling Consortium brought together mathematical modellers to do a model comparison exercise to see what the potential role is of HIV treatment as prevention in South Africa. The results are presented by Jeff Eaton at al. Finally, the article of Stephane Verguet is focussing on how best to assess the (cost-)effectiveness of different HIV treatment programs and models so that the existing limited resources can be allocated optimally.
The ability to estimate reliable HIV incidence rate ratios (IRRs) using cross-sectional data has vast public health importance in HIV surveillance and in prevention studies; it would reduce the need to recruit and maintain large and costly longitudinal cohorts. In fact, the most common method to evaluate HIV IRR is through cohort studies which are designed to estimate HIV incidence and the effects of interventions. However, the development of biomarkers which identify recently HIV infected individuals has made it possible to estimate HIV incidence using a cross-sectional survey. Following that, one study used classical statistical methods to analyse risk factors of recent HIV infection identified with a biomarker. It is therefore important to determine how that technology can be used to estimate incidence rate ratios.
This cross-sectional study examined whether sexual risk taking behaviours were impacted by knowledge of partner HIV status among HIV-infected South Africans enrolled in a primary care program. The study assessed four self-reported sexual risk behaviours as outcomes, namely current partner HIV status, reporting >2 sex acts in the last 2 weeks, reporting unprotected sex in Read More
The 6th IAS conference was held from 17-20 July 2011 in Rome. Although the conference is on HIV pathogenesis, treatment & prevention, the main focus this year was on the role of treatment in prevention. This prevention strategy can take different forms. First, by the immediate initiation of antiretroviral therapy (ART) after an HIV positive diagnosis, with a view to reducing a patient’s viral load and hence infectiousness. A second option is the use of a microbicide containing an antiretroviral, to reduce the probability of HIV negative people becoming infected. Finally, treatment as prevention can take the form of pre-exposure prophylaxis (PrEP) whereby antiretrovirals are used by individuals at high risk of exposure to HIV infection. The interim results of the FEM-PrEP trial showed that Truvada does not have a protective effect in women. But at the IAS conference the results of two new studies (the Partners PrEP trial and the TDF2 trial) on the use of oral PrEP in heterosexual people were extensively discussed. For these trials it was estimated that PrEP reduced the risk of transmission by between 62 and 78%.
Living in single-sex hostels, separated from their girlfriends, wives and children, and with few or no alternative to turn to, binge drinking and commercial or sex are common choices for recreation among mineworkers in Southern Africa. Binge drinking facilitates the acquisition and transmission of HIV and other sexually transmitted infections due to increased sexual risk behaviour. To explore the potential of preventing new HIV infections among mineworkers by reducing binge drinking in this population, a mathematical model was developed that aims to capture the causal associations between binge drinking, sexual risk behaviours and HIV incidence.
Randomised controlled trials (RCTs) are used to evaluate HIV prevention methods conducted among populations with a heterogeneous risk of HIV infection among individuals. This heterogeneity is an underestimated problem which should be taken into account when designing and interpreting RCTs that test prevention methods of HIV heterosexual acquisition in adult sub-Saharan African populations with a high HIV incidence. When the effects of tested interventions are rapidly reversible, the use of the crossover design instead of a parallel design should be considered.
The focus of this paper is to evaluate PrEP alongside ART and condom-use interventions in South Africa, informed by national HIV and demographical surveys. The age-structured model we developed pays close attention to the distribution of relative infection risks between age categories. It includes dynamical effects usually not explicitly modelled, such as age-dependent condom use and partner choice. Despite some the limitations of the model, the model offers a relatively simple approach to studying the impact of PrEP in the context of national and generalized HIV epidemics. The inclusion of an age variable offers a direct way of studying age-structured prioritising strategies.