HIV in SA: Seven graphs that tell the story

HIV in SA: Seven graphs that tell the story

By Marcus Low and Sean MacDonell

The recently published outputs of the Thembisa mathematical model (version 4.2) of HIV in South Africa paint a remarkable picture of the history of HIV in this country. For the period from 1990 to 2019, we’ve plotted seven graphs below using the estimates published on the Thembisa website. For all the graphs, a solid line indicates data which have been ‘matched’ against available survey data, while a dashed line represents data that are more uncertain as they are the Thembisa model’s projections or ‘best guesses’ based on previous trends in the data. A shaded region surrounding a line represents the upper and lower estimate (or 95% confidence interval).

Life expectancy

This graph shows life expectancy at birth in South Africa. It shows a dramatic drop to 53.2 as the HIV epidemic grew to its peak in 2004. The impressive increases since then has been attributed to the wide rollout of ARVs by the state (see next graph). This graph also makes it clear that, impressive as these increases are, they are only a relatively modest improvement on pre-HIV levels. Life expectancy in 1994 was 62; 25 years later in 2019 it is estimated to be 66.5.

Antiretroviral treatment (ART)

This graph shows the total number of people in South Africa receiving antiretroviral treatment. Comparing this to the previous graph, notice how dramatically life expectancy increased as antiretrovirals (ARVs) became more widely used from the mid-2000s.

Number of new infections and HIV deaths

The blue line on this graph shows the number of new HIV infections in South Africa by year. The good news is that the rate of new infections is decreasing from its peak of around 570 000 per year at the turn of the century. The red line represents HIV deaths per year and shows that yearly deaths peaked in 2005 at around 284 500 and then started declining (note the similar time that ARVs became more widely used in the previous graph). Notice how the red line is lower than the blue line – in other words, more people are becoming newly infected with HIV than people are dying of HIV. The result of this, as we will see in the next graph, is that the number of people living with HIV in South Africa is increasing. (Not shown on the graph: by 2019 a total of around 3.6 million people have died of HIV-related causes in South Africa.)

Number of people living with HIV

This graph shows the number of people living with HIV in South Africa. That this number is continuing to increase is both a bad and a good thing. As we can see from the previous graph, this effect is driven by the still high rate of new HIV infections (bad) and by the fact that people living with HIV are living longer and no longer dying at the same rates as before (good).

HIV prevalence

This graph shows HIV prevalence in South Africa. It is worth including here since HIV prevalence figures are often quoted in the media. Prevalence in this case is an indication of the percentage of the population who are living with HIV in a particular year. Prevalence is driven by the same forces driving the total number of people living with HIV (shown in the previous graph). The one key difference is that it also factors in that the total population of South Africa is growing. If you extend the model’s predictions into the future, HIV prevalence is expected to stay at around 12.9% until 2024, when it is anticipated to start coming down slowly – while the total number of people living with HIV is anticipated to keep increasing to around 8.2 million by 2030.

Viral suppression

This graph shows the percentage of people living with HIV in South Africa in whose bodies HIV has been suppressed to the extent that they are essentially non-infectious. It suggests that from 2018 more than half of all people in South Africa who are living with HIV are non-infectious. It also indicates that by 2018 the virus was not suppressed in around 46% (over 3.4 million) people living with HIV in South Africa – getting more of these people onto treatment and virally suppressed will be critical to reducing the rate of new infections.

A telling ratio

One way to assess South Africa’s HIV response is to compare the rate at which people are started on antiretroviral therapy with the rate at which people are becoming newly infected. If more people are being started on treatment than becoming newly infected, things are going in the right direction. This graph shows the ratio between these two numbers. It indicates that the rate at which people were starting ART only became greater than the rate of new infections in 2009. As long as we keep this ratio above 1 (the horizontal line) we are generally making progress – although the higher we can get it the better.

You can download these seven graphs as slides here.

Note: The graphs in this article were produced using RStudio and the ggplot2 package. Graphs are exclusively based on publicly available Thembisa model outputs. Spotlight takes full responsibility for any errors or misrepresentations there may be in the graphs.