Malaria diagnosis and mapping with m-Health and geographic information systems: evidence from Uganda

This article discusses how m-Health ("mobile-health", referring to the use of mobile and other wireless technology in healthcare) technologies and GIS can be used to improve access to medical services in Uganda's rural regions, where malaria prevalence is high and a significant portion of the population is not able to receive proper treatment. Once carried out successfully in Uganda, it is likely that these methods can be adjusted and used to scale in other countries around the world to reduce a variety of diseases. Using GIS, this study investigates where in Uganda malaria affects the largest number of people and where the application of m-Health protocol based on the available mobile network would have the highest impact. It also stresses the importance of continued diffusion of information and communication technologies (ICT) that would provide cheap, efficient, and geo-referenced data transmission for timely and effective response to disease outbreaks in all regions, but particularly rural regions.

Figure 2 below shows the number of malaria cases per year per hectare in Uganda, and figure 3 shows the area covered 2G and 3G mobile network coverage and the area covered by 3G mobile network coverage alone. Figure 4 shows the number of potential m-Health cases that could be covered by increased mobile network accessibility and the implementation of m-Health strategies.







As seen in Figure 3 and 4, the implementation of m-Health strategies could have a significant impact on accessibility to treatment in remote populations, particularly in Uganda's west and central-southeast regions. After analyzing which regions suffer the most from malaria outbreaks, mobile network creation and improvement efforts can be made in these specific regions to vastly improve access to  low-cost, reliable and safe diagnostic protocol, as well as reduce overcrowding and contamination potential in health facilities.

Larocca, A., Visconti, R. M., & Marconi, M. (2016). Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda. Malaria Journal, 151-12. doi:10.1186/s12936-016-1546-5