Agent-based modelling, also called microsimulation, is a way of modelling epidemics that is growing in popularity. Instead of the traditional way of modelling using differential equations, an agent-based model consists of, perhaps, thousands of agents, each representing a person, and each behaving according to a simple set of rules. Instead of outputs such as infection and mortality rates being derived from equations, they are derived from the interactions of the agents over many iterations. These models are providing rich insights into the HIV epidemic.
UNAIDS has reported that the prevalence of people infected with HIV but who are not on ART, the incidence of HIV, and AIDS related mortality are falling. The Health Metrics Institute recently made their own, semi-independent, assessment of the trends in each of these indicators and reached similar conclusions with small differences arising from the use of somewhat different assumptions. Both analyses suggest that the world is on track to end AIDS by 2030, but this will depend on continued expansion of treatment at about the present rate together with supportive prevention efforts in Sub-Saharan Africa. Unfortunately, the data on which these analyses are based is weak in almost all places and better data on patient monitoring, follow-up and support, including drug procurement, supply and delivery, and better routing surveillance are needed.
The recent HSRC household survey reports that the HIV prevalence among adolescents and young people is declining. Although the decline is important, the focus needs to be on the fact that the reported HIV prevalence levels are still very high, together with alarmingly high levels of HIV incidence. Prevention methods have demonstrated effectiveness in reducing the risk of HIV acquisition among many of the most-at-risk populations. More research is needed, however, into how HIV is spread among the adolescent population and how to decrease this spread.
Individuals across Africa may have changed their sexual behaviour following the visibility of AIDS in the public sphere in the mid to late 1990s. Though each change in behaviour may have been small, the changes affected simultaneously different aspects of individual sexuality, and added up cumulatively into a moderate reduction in sexual behaviour at the individual level. In turn, this change in individual behaviour was translated into massive disruption of sexual networks at the population level. This made it difficult for HIV to propagate in the population leading to large declines in HIV incidence and prevalence.
Household contacts of active TB cases are at increased risk of TB infection and several studies have measured TB prevalence in this key population. The study described here not only measured TB prevalence, but also measured TB and HIV incidence in the household contacts of 729 TB index cases in the Matlosana sub-district in North West Province. We concluded that the efficacy of contact tracing for TB control purposes might be improved by a second intensified case finding visit and by providing preventive treatment against TB for both HIV-infected and HIV-seronegative household contacts of TB cases.
Currently we are faced with two major threats from viral diseases: Over the last 30 years HIV has spread across the world and continues to plague us. Over the last 3 months the hemorrhagic fever caused by the Ebola virus has spread across West Africa killing thousands of people. If we are to contain HIV in the long-run and Ebola, hopefully, in a much shorter time, this will depend on our ability to understand the nature of the threat and the strategies of the disease causing organisms.
Epidemiological models for describing how a disease spreads through a population have been extremely useful to reduce the number of individuals who get sick or even die from illness. Developing meaningful and useful models is not easy however. In this paper, we first motivate the use of agent-based modelling and secondly, we present common challenges associated with agent-based modelling (of HIV) and our approaches to dealing with them.
Expanding ART coverage to healthier HIV patients is widely regarded as a potential strategy for addressing the rampant TB epidemic in high HIV-TB burden settings. Estimating the population-level impact of ART expansion on TB disease has proven challenging. We set out to estimate the potential effects of changing HIV treatment policy on TB outcomes in South Africa, comparing the results of three independent TB models. This project was part of a broader effort to shed light on the consequences of HIV policy changes, through model comparison and consensus building, a process pioneered in the HIV modelling field by the HIV Modelling Consortium.
Existing approaches to TB control have been no more than partially successful in areas with high HIV prevalence. In the context of increasingly constrained resources, mathematical modelling can augment understanding and support policy for implementing strategies most likely to bring public health and economic benefits. Recognising the urgency of TB control in high HIV prevalence settings and the potential contributions of modelling, the TB Modelling and Analysis Consortium (TB MAC) convened its first meeting between empirical scientists, policy makers and mathematical modellers in September 2012 in Johannesburg. Here we present a summary of results from these discussions, as well as progress made in South Africa.
On the occasion of AIDS 2014, the twentieth International AIDS Conference in Melbourne, SACEMA released a policy brief on the ongoing debate about appropriate initiation of antiretroviral therapy for HIV positive people.