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 HIV epidemic is becoming financially unsustainable. It is therefore essential to assess the effectiveness and cost-effectiveness of different HIV treatment programmes and models so that the existing limited resources can be allocated optimally. Data are gathered periodically to measure the retention of patients on ART after treatment enrolment at the national level, though this data collection is often complicated by patients lost to follow-up. However, little work so far has assessed the performance (effectiveness and cost-effectiveness) of ART programs differing by the kind of providers and subsequently identified the “good” versus “bad” performers. Identifying the determinants of good performance for ART programmes is essential. Decision-makers will then be able to potentially improve ART delivery in countries.
Many mathematical models have investigated the impact of HIV treatment as prevention in combination with other prevention strategies or other guidelines for HIV treatment provision. Generally, all models have predicted positive prevention benefits of HIV treatment, but directly comparing the results of different models has been challenging because each model has been used to answer different questions and has reported different key outcomes. In November 2011, the HIV Modelling Consortium convened a meeting with the aim to understand the extent to which different mathematical models agree about the potential impact of HIV treatment. The results of a model comparison exercise – in which each of the models simulated a standardised set of HIV intervention scenarios and reported common metrics of intervention impact – are reported here.
Household surveys estimate the proportion of HIV infected persons in KwaZulu-Natal at a level of ~23% of the population. What is urgently needed is to seek ways to reduce HIV incidence while caring for existing infections in KZN. The emerging course of action against HIV spread is to use a combination of prevention interventions rather than relying on individual tools. This article discusses mathematical modelling conducted to forecast the impact of combined interventions at both the short- and long-term. The modelling shows the importance of repeated high coverage of testing, linkage to care, starting treatment on time (at CD4 count 350 or less), and high coverage of circumcision in order to reduce the rate of HIV infection in KZN.
In December 2011 Jon Cohen published an article in which he discussed the prospects for halting the epidemic of HIV/AIDS (1). He highlights the important observation that, due to recent evidence on effective interventions to prevent HIV, we have for the first time the means by which to end the AIDS epidemic, provided of course Read More
Although antibiotics have saved millions of lives, their use and misuse has often led to the development of resistance in the agents that they are intended to fight. SACEMA's Brian Williams recently published a commentary on an article in published in Science Translational Medicine in which Sergeev et al. used dynamical models to investigate the Read More
In the June 2010 issue of the SACEMA Quarterly, Steve Bellan reported on the 2009 and 2010 Clinics on the Meaningful Modelling of Epidemiological Data (MMED) that were given at the African Institute for Mathematical Sciences (1). This clinic continues to be given annually and in April 2012 an article has been published in PLOS Read More