Diseases – like the examples of trypanosomes and HIV/AIDS – are not only perceived as causing negative effects; they also create jobs for people. Hence some people get nervous about what they are going to do when these diseases are under control. And is the latter actually going to happen?
Abstract: Twenty years ago, in 1997, I wrote the following piece reflecting on the Mothusimpilo project, an early attempt to understand and help to manage the epidemic of HIV in South Africa. I thought it might be interesting for you to look back on where we have come from.
The history of sub-Saharan Africa has been defined and determined to a large extent by the struggle against tropical diseases, many of them vector borne, including malaria, leishmaniasis, trypanosomiasis and many others. To add to this burden our continent has now to deal with the ravages of HIV and the consequent rise in tuberculosis. In this issue of the SACEMA Quarterly we discuss some of the key problems and ways in which we might be able to address and mitigate some of the challenges that we face in this regard.
This article is based on the presentation given by John Hargrove at the NRF Science for Society Lecture entitled Ending HIV/AIDS in South Africa held on 1 December 2016 in Stellenbosch. He argues that the proactive use of ART (Treatment as Prevention or TasP) provides a powerful weapon for combatting the HIV epidemic, and that we also have the tools for monitoring and evaluating the progress of that programme. Mathematical modelling has played an important role, both in suggesting appropriate interventions, and in developing new monitoring methods, but we are still in for a long journey.
With the release of the WHO Consolidated Strategic Information Guidelines , countries are provided with a template, in the form of a depiction of the “Care Cascade”, permitting them to quantify the state of care as it currently stands. The Care Cascade begins by characterising all infected individuals in a population, before illustrating the cascading loss of patients at each stage of care between diagnosis and viral suppression. Countries are now beginning to produce estimates of their national cascades in order to evaluate the efficiency of current care programmes. This article discusses data issues related to cascade reporting and suggests ways to improve reporting.
To fast-track the HIV response and end AIDS by 2030, the Joint United Nations Programme on HIV/AIDS (UNAIDS) called for 90-90-90 targets for 2020. Achieving these targets has resource implications – it will require increase in spending and efficient utilization of HIV funding and lead to savings by preventing illness, deaths, and new HIV infections. Thus, how countries decide to allocate and prioritize their HIV funding will directly impact whether end of AIDS is achieved. This article examines the pattern, source, determinants, and impact of HIV spending on care and treatment from 2009 to 2013 in 38 LMICs, which are home to 73% of PLHIV.
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.
A new formal ‘R Package’ to support incidence estimation is available on the Comprehensive R Archive Network (CRAN). This is the canonical way that the R community distributes stable packages to share functionality, and it is the heart and soul of the R coding environment. The new release through CRAN will make a substantial range of functionalities around incidence survey design and survey data analysis seamlessly and flexibly available to any skilled R programmer/analyst.
The remarkable expansion in access to ART globally since 2004 has transformed HIV from a life-threatening into a chronic illness. Improved survival as a result of ART has starkly highlighted the lack of preparedness amongst health systems to deal with the complex needs of children living with HIV as they grow older and enter adolescence. While the drive to increase coverage to ART needs to continue, there is also an urgent need for policymakers and healthcare providers to focus beyond the goal of prolonging survival and to concentrate ensuring that adolescents living with HIV achieve an optimum quality of life.
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.