The end of AIDS: possibility or pipe dream The end of AIDS: possibility or pipe dream? A tale of transitions Alan Whiteside and Michael Strauss Slides to back up the article in African Journal of AIDS Research Vol 13 Issue 2 2014 http://www.tandfonline.com/raar 5 - 6 December 2013 These slides were presented in Cape Town at the Structural Drivers of HIV Conference in December 2013 and form a visual picture for our article.

Years of life lost (women) by cause: Global, 2010 We all know the saying that a picture is worth 1000 words so here are some pictures. As you can see globally there are many years lost among infants and children. As people age we begin to see cardiovascular disease and cancers accounting for life lost. There is quite a significant burden of malaria particularly among younger people. The burden of AIDS and TB peaks among young adults. Keep your eyes on the yellow. 0-1 1-4 5-14 15-24 25-49 50 – 80 + Age Source: 2010 Global Burden of Diseases Study http://www.healthmetricsandevaluation.org/

Years of life lost (women): Western Europe 2010 Maternal Neonatal HIV & TB There is no yellow in the next slide which shows years lost among women in Western Europe. 0-1 1-4 5-14 15-24 25-49 50 – 80 + Age Source: 2010 Global Burden of Diseases Study http://www.healthmetricsandevaluation.org/

Years of life lost (women): Southern Africa, 2010 Maternal Neonatal HIV & TB Central Africa has appalling child mortality and AIDS is a growing burden. The impact of AIDS and TB increases in central Africa, but to see the full effect of this horrible disease we have to go to Southern Africa. 0-1 1-4 5-14 15-24 25-49 50 – 80 + Age Source: 2010 Global Burden of Diseases Study http://www.healthmetricsandevaluation.org/

Understanding curves: new Infections and deaths I now come to the core of my presentation. I want to talk about two tipping points, an economic one and an epidemiological/ advocacy one. Note I have not put figures on either axis [BUTTON] The number of new HIV infections for any epidedemic looks something like this. The number of HIV deaths looks something like this. [BUTTON] Everyone who is between these two curves will need treatment, this is certain [BUTTON].

Treatment requirements People Requiring Treatment We all know about the different opinions about when treatment should be initiated, and who really needs treatment, but for the remainder of this presentation, when I talk about people needing treatment, I am really talking about everybody living with HIV that is not currently receiving treatment. You noticed that as long as the two lines do not cross the size of the pool of people needing treatment will continue to grow. This is a nightmare for both the health sector and the finance ministry. This is not original work it was put forward by Mead Over of the Center for Global Development in Washington.

Treatment requirements Incidence Attrition People living with HIV (needing treatment) People currently receiving treatment Here is another way to picture the situation [BUTTON]. The pool of people who are HIV infected and who will eventually require treatment is fueled by incidence and is growing. [BUTTON] The number of people currently receiving treatment is also growing as people are initiated on to therapy [BUTTON] ; while the pool of people requiring treatment is emptying out thanks to treatment initiation. Unfortunately there is attrition from the pool of people on treatment. [BUTTON] When people cease to take treatment for whatever reason they return to the pool of people requiring treatment. [BUTTON] Of course there is also attrition by death from both pools. Death is inevitable, but we certainly don’t want to try to increase the number of deaths to empty out these two pools. [BUTTON] Our way forward is to focus on decreasing incidence and attrition, while making sure we keep putting more people on treatment every year. Initiation on ART Death Death

Economic Transition Credit Mead Over What we want is to achieve an economic transition where the number of new infections [BUTTON] falls below the number of deaths [BUTTON]. At this point the ministries of health and finance can breathe sighs of relief [BUTTON] as the future is predictable and the number of people living with HIV and AIDS is decreasing. The economic tipping point has been reached.

Epidemiologic transition Epidemiological Transition Programmatic Transition I should like to talk about two more lines we can add to the graph which allows us to think about an epidemiological and programmatic transition [BUTTON X3]. The green line is the number of new people initiated on treatment. [BUTTON] The purple line is the number of people from the HIV infected pool requiring treatment in at a point in time. This will be lower than the number of new infections (because of death). [BUTTON]. I would argue that there are two tipping points on this graph. They are somewhat artificial but none the less they can be modeled, graphed and celebrated. At the moment I am calling them epidemiological and programmatic transition points. [BUTTON] The first is when the number of people initiated on treatment exceeds the number of people needing treatment. Then we are winning somewhat. [BUTTON] but when the number of people initiated on treatment exceeds the number of new infections we are really winning. [BUTTON] And if you run this you can see why. With treatment the number of people dying declines [BUTTON]; but so do the number of new infections [BUTTON]. So the faster we put people on treatment [BUTTON] the sooner we reach the economic [BUTTON] and epidemiological [BUTTON X2] transitions. Thus saving time and lives. That is the theory and I would argue these graphs can be applied to any country or HIV epidemic.

Epidemiologic transition And if you run this you can see why. With treatment the number of people dying declines [BUTTON]; but so do the number of new infections [BUTTON]. So the faster we put people on treatment [BUTTON] the sooner we reach the economic [BUTTON] and epidemiological [BUTTON X2] transitions. Thus saving time and lives. That is the theory and I would argue these graphs can be applied to any country or HIV epidemic.

Real data from South Africa ASSA 2008 – Comparing the estimates to the latest HSRC data: Prevalence is higher than ASSA estimates for 2012 There were fewer AIDS deaths than predicted in 2012, possibly due to drug improvements Incidence rates are in 2012 were higher than ASSA estimates In 2008, the benefits from treatment as prevention were not fully understood What about using real numbers! So we used the ASSA 2008 model data for South Africa. SOME CAVEATS

Real data from South Africa the first slide is a quick overview of the epidemic. It shows the number, by year, of infections, AIDS sick and deaths from the beginning of the epidemic to 2025 – not a comforting picture. These figures are in the millions.

Real data from South Africa No Economic Transition on the horizon so what about applying the transition ideas to real data, first the bad news. [BUTTON] The economic transition is not even on the horizon.

Real data from South Africa let’s look at the number of new people that will eventually need treatment (this is essentially a graph of the boxes we looked at earlier). As I have already shown, this is slightly more complicated than simply looking at incidence, shown by the blue line here. People with HIV or AIDS that have died – for whatever reason – will no longer require treatment. [BUTTON]

Real data from South Africa The purple line shows incidence minus AIDS deaths. Using the ASSA 2008 estimates, this purple line is going down quicker than we expect because of higher estimates of AIDS deaths than what we now know to be true. [BUTTON]

Real data from South Africa The discovery of treatment, and its rollout marked a significant victory and the number of new treatment initiations each year climbed quickly between 2005 and 2010. The green line shows estimated new initiations on treatment. Unfortunately, retention of patients in ART programmes is not as high as we would like. There are some people that were initiated on ART, but were lost from the programme. These people will ultimately need to go back on treatment at some point. [BUTTON]

Real data from South Africa Sustained financial and political comittment means we will catch up Epidemiological Transition Programmatic Transition The number of new people that will eventually need treatment is thus equal to incidence minus deaths, plus attrition – the yellow dotted line on the screen. But there is some good news. When we look at the pool of new people that will eventually need treatment compared to the number of new people initiated on ART, we can see that the two lines crossed in 2006 [BUTTON]. This means the pool of people needing treatment is emptying year on year (albeit slowly). The ASSA estimates show that the second epidemiological and advocacy transition I talked about occurred around 2010 [BUTTON]. We also now know about the benefits of treatment as prevention, and the blue line of incidence is unlikely to cross over the treatment line again, as is shown in this picture. [BUTTON] This shows that we are putting more people on treatment than the number of new people that will need treatment each year. We are catching up. [BUTTON]. It may seem that the message here is to increase commitment to treatment. But really what these slides show us that if we can decrease either incidence or attrition or both, the number of new people being treated will increasingly exceed the number of new people that will need treatment, and we catch up on treatment needs quicker.