Background

As a data analyst i was provided with a practical guide for using a geographic information system (GIS) to integrate, visualize, and analyze geographically-referenced data extracted from the Demographic and Health Surveys (DHS) and other key data sets to facilitate monitoring and evaluation (M&E) of HIV/AIDS and related health programs. Dataset was made accessible to me without commercial GIS software licenses.

Goal

Use the free and open source GIS software package, QGIS, to perform essential GIS tasks needed to respond to typical M&E questions as it relates to HIV/AIDS health program in Rwanda.

Methodology

Using created choropleth (color-shaded) map of a single indicator. Although maps of single indicators can be quite useful, to see the potential associations between multiple indicators it is important to be able to map more than one variable at a time. Then generate a multi-indicator maps by using pie charts, bar charts, and proportional symbols for one variable superimposed on a choropleth map showing the geographic distribution of a second variable.

QGIS and several plugins is needed to be installed on your machine. and also the required dataset as provided by USAID to be downloaded.

Key Insights

• The map shows that at the district level in Rwanda, according to the Rwanda DHS 2010, the majority of contraceptive methods used by married women were modern (yellow), although a large proportion of married women were using no method of contraception (brown).
• The map also allows a few observations regarding the relationship between female HIV prevalence and the choice of contraceptive methods among currently married women. The darkest districts, which represent the highest prevalence of HIV among women of reproductive age, encompass the City of Kigali, which is located in the center of the country. Although traditional methods of contraception (blue pie slices) are used much less often in Kigali, they appear to be used more widely in Kigali’s southern
• As one would expect, given that female HIV prevalence is strongly correlated with total HIV prevalence, the size of the symbols representing female HIV prevalence increases relatively consistently with increases in total HIV prevalence.