Dynamic changes of the AIDS mortality rate

Related Work

The illustration and monitoring of the global mortality rate of AIDS and HIV has been the subject of numerous studies since the first epidemic outbursts of the disease.
John Bongaarts (1996) looked at global trends in the AIDS mortality rate at a very early stage of data collection. He illustrated the dynamic changes between 1980 and 1995 for the different world regions. Since Sub-Saharan Africa is a region of high interest he also looked at the HIV infection rate illustrated with a map. Ortblad et al. (2013) took a similar approach by looking at the temporal changes in the AIDS mortality rate between 1980 and 2010. They illustrated a temporally complete timespan but did not set their focus on regional differences. Their goal was to investigate the extent to which AIDS mortality contributes to the total number of deaths worldwide. On a map, they could illustrate the regions or countries where AIDS gained overall contribution as a cause of death (Ortblad et al. 2013). This approach of looking at the contribution of AIDS/HIV mortality to the total burden of disease mortality was also used in previous studies. Christopher Murray (1997) even made predictions about these changes for the year 2020. His predictions match up with the findings that Ortblad (2013) presented in his paper. Newer predictions even allow further outlooks into the future as far as 2030 (Mathers et al. 2006). In his findings Colin Mathers (2006) illustrates nicely how AIDS as a cause of death will gain significance compared to other fatal diseases. Even though Mathers (2006) findings are high in the temporal resolution he takes his own classification of local differences between countries. He does not classify based on spatial differences, but based on the average income of a country or region. Hence the variation of predicted AIDS mortality rates between low- and high-income countries are visualized in separate graphics. This gives a new perspective on the topic and is a good example of how the data may also be interpreted (Mathers et al. 2006).
All these studies focus more on the temporal scale of the issue but pay less attention to the spatial aspect. The southern African region especially has the highest AIDS mortality rate of all the global regions (Ferrand et al. 2010). For this reason the Sub-Saharan region is the global focus of extensive studies on a variety of perspectives of the problem. Granich et al. 2015 only looked at the top 30 countries with the highest AIDS mortality rate of which more than 20 are African countries. Granich (2015) not only looked at the mortality and infection rate but also at other factors, such as the effectiveness of treatment or the number of patients receiving treatment. For the chosen countries, a detailed map was created to display the number of AIDS related deaths per 1000 people living with HIV, illustrated in different classes. He presents a very nice example of how the data can be analysed. Since almost two thirds of the countries with the highest AIDS mortality ration are located in the Sub-Saharan region, in this part of his studies the spatial resolution is high (Granich 2015). Other studies look at differences between male and female mortality, like Idele et al. (2014). This study concentrated more on the differences between age groups but again on a higher spatial resolution than the studies of Ortblad (2015) and Bongaarts (1996) for instance. Idele (2014) included global statistics on the total number of adolescents that are living with HIV. He separated the Sub-Saharan region like Ortblad did before, hence also including the bigger picture in his findings. Only one study included north African countries in their findings, probably because of their relatively low AIDS mortality rates. Zayeri et al. (2016) illustrated AIDS mortality rates of different countries in a very basic way. The graphics they use could be much improved by a better-arranged view of the temporal data. Some of the studies don’t use any graphics to present changes in the mortality rates (Ferrand et al. 2012). They used a more numerical approach but mainly focused on South- and Southeast Africa (Ferrand et al. 2012)
The United Nation Programme (UNAIDS) shows a huge interest in the issue of the development of the AIDS mortality rate. They rely on crucial information such as presented in Stover et al. (2006), for instance the gender ratio of HIV infections as well as the age distribution of the infected. Stover (2006) included data from specific countries on a high spatial resolution and considered the temporal changes in the years since the start of the epidemics as well. Alexandra Jones (2014) presented some updated numbers and some key factors to prevent the further epidemic of HIV. However, in her findings she does not use any kind of illustrations nor are any dynamics visible.
As we have seen, there are some approaches that look either into a high temporal resolution of the AIDS mortality rates like Murray (1997) or Mathers et al. (2006), while other studies focus on a finer spatial resolution like Ortblad (2013) or Granich et al. (2015). So far, many studies conducted their spatial resolution based on different countries. Only a few of them have started to look at local or regional differences on an even finer resolution. This is a gap that should be filled in future work as well, since preventive measurements are to be introduced in regions where there is a higher need for it. However, there is a lack of studies that combine both high temporal and spatial resolutions to capture the whole dynamic in the changes of the AIDS mortality rate. We find it important to combine these aspects and hope to contribute with our work to a finer picture of the issue for the African region where the problem is most severe.

Project of Geo 878 FS2017