One question that had not been answered in this area was whether the distance that an individual had to travel to access voluntary counselling and testing made a difference to their attendance. Although the answer may seem to be obvious (that the closer you are to a clinic the more likely you are to attend) evidence is needed to confirm this. Because this is a spatial question, employing geographic technologies is appropriate and useful.
Over the past few years, GPS coordinates have been taken for many of the 5,000 households in the study area. This provided latitude and longitude coordinates so that each household could be mapped using GIS, as shown in figures 1 and 2.
Once the data were mapped, it was possible to answer the question, ‘does distance from clinic affect attendance at voluntary counselling and testing?’
GIS is a powerful tool with many applications and the toolbox provided a way to measure the distance of all households to their nearest clinic. With so many households this would have been very tedious and inaccurate by hand.
Once all the distances had been calculated by ArcGIS, a statistical analysis was performed, specifically a logistic regression, using a programme called STATA.
"Does distance from clinic affect attendance at voluntary counselling and testing?'
Figure 1: Households and clinics in study area.
Figure 2: Map to show households, clinics and transport links.
The results showed that people who lived in households further from the clinics were less likely to attend VCT - in fact for each kilometre away from the clinic the likelihood of attending decreased by over 25%. In geography we call this effect ‘distance decay’ i.e. the interaction between two places declines with distance between them.
Further analysis of another variable, whether distance made a difference to attending the clinic at all, showed that those living further away were actually more likely to attend the clinic. This may sound counter intuitive but further investigation showed that villagers living further from clinics were offered a car to get to the clinic and this was a major motivator. Travelling by car meant that people could bring their children for a health check or carry home heavy items they bought at the market. This example provides justification for evidence- based research which sometimes produces answers that we least expect.