A new data set on the HIV epidemics in each country since 1979 is now available in Gapminder World. The dataset is an expansion of the excellent UNAIDS data, and illustrates several interesting points.
Here is a moving graph with the percent adults infected with HIV in each country plotted against the GDP per capita. The size of the bubbles shows the number of people infected with HIV in each country (not the total population, as is usual in the Gapminder graphs). Click Play to see the epidemic from 1979 to 2007, and to see new surprising trends.
The epidemic is levelling off, but at a tragically high level.
Recently the epidemics are levelling off in many countries, and, indeed, at the overall global level. In some of the worst affected countries there is a fall in the percentage of infected adults. However, keep in mind that in countries such as Botswana that have been quite successful in providing treatment for those infected, the death rate due to AIDS has fallen and therefore they still have quite a high percentage of infected people even if the number of new infections is falling.
Below is a screen-capture with some examples of this reversed trend. As before the Y-axis represents the percentage of the adult population that is infected, although a logarithmic scale is used to make it clearer. The X-axis represents GDP per capita and the size of the bubbles represents the number of people living with HIV. Note however, that the colour in this graph shows the year, so that red bubbles display the situation in 2007, orange bubbles the situation in the 1990s and the yellow bubbles the situation in the 1980s.
Click here to get to the interactive version of the graph.
HIV is highly concentrated in a few countries.
In a dozen countries 6 percent or more of the population is infected with HIV. All of these countries lie in southern and eastern Africa. Below is a world map where the red colour signifies a high percentage of adults infected, and blue a low percentage. The size shows the number of people infected. Here is a link to the interactive map, where you can see the change over time.
Note the geographical pattern, with most of the red and orange bubbles in southern and eastern Africa. Note also that the percentage of infected people is lower in west and north Africa. The very high percentage of infected people is definitely not a general African phenomenon.
The high percentage of the total population infected with HIV in southern Africa results in a high number of total infected individuals in most of these countries, as depicted by the big size of the bubbles in that region. However, there are also many countries with a much lower percentage of infected people that have a large total number of infected individuals, simply due to the large total population. India is one such example. Likewise, Russia has “only” about one percent infected; however that means that almost a million Russians live with HIV.
The 12 countries in southern and eastern Africa which are affected the worst by the HIV epidemic only account for 4% of the world population, but 50% of the people worldwide who are infected with HIV live in these 12 countries. What are the reasons for this geographical pattern? Read the latest report from UNAIDS.
About the data
The dataset is mainly based on the excellent dataset released by UNAIDS. To increase the understanding of the pattern of the epidemic Gapminder has complemented the UNAIDS dataset with some different estimates:
- Estimates going back to 1979 have been added (the UNAIDS data starts in 1990).
- Estimates for a dozen smaller countries have been added.
- More elaborate estimates have been done for 15 high-income countries, replacing the UNAIDS data for these countries.
Here is a link to Gapminder’s documentation for the data (Gapminder Documentation 006).
Click here to download the “HIV infected (% of adults aged 15-49)” indicator. Click here to download the “people living with HIV” indicator. You can always download any of the Gapminder indicators by clicking on the “list of indicators” button to the left of the graph.
The new data for the two indicators replace the data we used until now. The previous data were taken from the World Development Indicators.