We assess here the potential effect of expanded HIV treatment for the prevention of AIDS-related deaths. We analyzed the available UNAIDS data to describe AIDS-related deaths, ART coverage and new HIV infections in 30 countries with the highest AIDS mortality burden and compared it with data from eight high-income countries. For illustrative purposes, we also explored the potential impact of reaching international treatment expansion targets in South Africa and Nigeria- two countries with the largest HIV epidemics, but with different trends of AIDS-related deaths over time – through the examination of four treatment expansion scenarios.
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.
In 2011, the Ministry of Health in Swaziland joined forces with the WHO, the Global Fund and SACEMA to do the first in depth health programmes progress evaluation using triangulation from key empirical data sources. The focus was on key questions like: Given increasing coverage of ART, has ART reduced adult and/or infant mortality?; Can TB trends be related to trends in HIV prevalence, ART coverage and combined TB/HIV interventions?; Can trends in infant mortality be related to uptake of PMTCT?
Reliable mortality data are essential for planning health interventions, yet such data are often not available or reliable in developing countries, especially in sub-Saharan Africa. Health and socio-demographic surveillance sites, such as Agincourt in South Africa, are often the only way to assess and prospectively understand health trends at a population level, and thus have the potential to address this gap. This article summarises the main findings from my PhD in which advanced methods were applied to better understand the dynamics of age-specific mortality both in space and time, to identify age-specific mortality risk factors which have a high “impact” at a population level, and to relate inequalities in risk factor distributions to observed spatial mortality risk patterns.