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

Background\r\nRural populations experience several barriers to accessing clinical facilities for malaria diagnosis. Increasing penetration of ICT and mobile-phones and subsequent m-Health applications can contribute overcoming such obstacles.\r\nMethods\r\nGIS is used to evaluate the feasibility of m-Health technologies as part of anti-malaria strategies. This study investigates where in Uganda: (i) malaria affects the largest number of people; (ii) the application of m-Health protocol based on the mobile network has the highest potential impact.\r\nResults\r\nAbout 75% of the population affected by Plasmodium falciparum malaria have scarce access to healthcare facilities. The introduction of m-Health technologies should be based on the 2G protocol, as 3G mobile network coverage is still limited. The western border and the central-Southeast are the regions where m-Health could reach the largest percentage of the remote population. Six districts (Arua, Apac, Lira, Kamuli, Iganga, and Mubende) could have the largest benefit because they account for about 28 % of the remote population affected by falciparum malaria with access to the 2G mobile network.\r\n\r\nConclusions\r\nThe application of m-Health technologies could improve access to medical services for distant populations. Affordable remote malaria diagnosis could help to decongest health facilities, reducing costs and contagion. The combination of m-Health and GIS could provide real-time and geo-localised data transmission, improving anti-malarial strategies in Uganda. Scalability to other countries and diseases looks promising.