Using mathematical models to understand the potential of early treatment to reduce HIV transmission

Is it possible to control the epidemic of HIV by using antiretroviral therapy? This pressing question is addressed in a collection of new articles published in the open-access journal PLoS Medicine.

The collection of articles was written by members of the Gates funded HIV Modelling Consortium, which aims to help improve scientific support for decision making by co-coordinating a wide range of research activities in mathematically modelling the HIV epidemic.

A number of researchers from the South African Centre for Epidemiological Modelling and Analysis (SACEMA) based at Stellenbosch University (SU) contributed to the collection of papers. SACEMA hosts the secondary secretariat of the HIV Modelling Consortium, which is centrally based at Imperial College London (UK).

The PLoS Medicine collection will be launched two weeks before the 19th International AIDS Conference (AIDS 2012) in Washington DC, to be held from 22 to 27 July 2012. The articles use mathematical models as the basis to provide insights into the feasibility of interventions, their potential epidemiological impact and affordability, and recent scientific observational studies and community trials, which will support evidence-based decision-making on the use of antiretroviral treatment to prevent HIV transmission.

The background to this collection is a November 2011 meeting in Stellenbosch, which focused on the cross-cutting issues that affect the impact of new scientific findings about HIV treatment preventing new infections.

As the introductory article “HIV Treatment as Prevention: Models, Data and Questions Towards Evidence-based Decision-Making” explains, over the past two years there have been several positive advances in HIV prevention research.

In particular, the authors say: “The finding that has created the greatest excitement has been that HIV-infected individuals who are given antiretroviral treatment (ART) are much less likely to transmit the infection to their heterosexual partners than those who are not.”

Currently ART is directed at those in greatest clinical need. Expanding the group of people treated would be a substantial change in health policy. It would also have a huge associated cost.

“The realisation that the two broad categories of ‘treatment’ and ‘prevention’ are inextricably linked is probably the most significant shift in thinking about both the social and biological approaches to the epidemic to take place over the last few years,” says SACEMA director Dr Alex Welte, one of the co-authors of the introductory article.

He believes that mathematical modelling, such as is being done at SACEMA, can significantly help to scientifically plot what the influence of treatment and prevention strategies can have on the broader characteristics of the HIV epidemic.

A great deal of information is needed in order to make efficient and ethical policy decisions regarding HIV ‘Treatment as Prevention’ (now commonly known by the acronym TasP). Mathematical models can help pull the information together and structure it in a way that will help policy makers understand the available options and their consequences, both epidemiological and financial. One focus of the collection is to evaluate the use of these models by assessing the level of consistency between them—and between the models and data collected from the real world.

The choice of which particular groups should be given priority when expanding access to ART to depends on a wide range of considerations, including, for example, which groups are easiest to access and which groups are most likely to reduce onward transmission. Decisions regarding HIV treatment as prevention are not only practical but ethical, argue leading authors in the series; as health policy on HIV prevention is limited by resource constraints, the authors review how to expand the provision of ART and who to expand it to.

In one of the articles in the collection of which SACEMA researcher Dr Wim Delva is lead author, the focus is on ways to optimise the impact of an expanded HIV Treatment Programme as a prevention strategy.

“Because of resource constraints we currently have to prioritise HIV treatment in our health policies,” explains Dr Wim Delva. “This is all done in an effort to maximise epidemiological and clinical benefit while still making sure that our plans are feasible, affordable, acceptable, and equitable.”

“Our models suggest that by prioritising access to ART treatment for specific groups, based on specific clinical and behavioural factors, these considerations can be maximised,”

In addition to the model based investigations of TasP, the collection contains an article, lead by SACEMA authors Dr Wim Delva and Dr Alex Welte, on methodological issues in constructing epidemiological scenario models. This aims to bridge the gaps that often arise between ‘producers’ and ‘consumers’ of scenario models, by providing a mutually digestible set of principles and guidelines.

* The PLoS Medicine collection, “Investigating the Impact of Treatment on New HIV Infections”, publishes two weeks prior to the AIDS 2012 conference in Washington D.C., which PLoS Medicine editors will be attending.

More about SACEMA and

The South African Centre for Epidemiological Modelling and Analysis (SACEMA), based at Stellenbosch University (SU), is a national research centre established under the Centre of Excellence programme of the Department of Science and Technology and the National Research Foundation. Although based at Stellenbosch University, its researchers and postgraduate students also work at various other institutions in South Africa.

The Centre focuses on research in quantitative modelling of the spatial and temporal patterns of disease. The immediate aim of the research is to understand and predict the development of various diseases, and thereby to provide advice on how best to combat them. Research themes include issues pertaining to HIV, TB and malaria, although not to the exclusion of other epidemiological problems.

Engela Duvenage, Media: Faculty of Science, Stellenbosch University
+27 21 808 2684 082 874 1291

Source: Stellenbosch University – Press Release – 17 July 2012