Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda
Abstract Background Rural 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. Methods GIS is used to evaluate the feasibility of...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2016-10-01
|
Series: | Malaria Journal |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12936-016-1546-5 |
id |
doaj-bf83b4f05f344604a044be72387cd170 |
---|---|
record_format |
Article |
spelling |
doaj-bf83b4f05f344604a044be72387cd1702020-11-25T00:47:45ZengBMCMalaria Journal1475-28752016-10-0115111210.1186/s12936-016-1546-5Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from UgandaAlberto Larocca0Roberto Moro Visconti1Michele Marconi2Cosmo Ltd.Università Cattolica del Sacro CuoreResearch and Consulting GIS, Natural Resources Management, Marine Ecology, Disaster Risk ReductionAbstract Background Rural 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. Methods GIS is used to evaluate the feasibility of m-Health technologies as part of anti-malaria strategies. This study investigates where in Uganda: (1) malaria affects the largest number of people; (2) the application of m-Health protocol based on the mobile network has the highest potential impact. Results About 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. Conclusions The 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-localized data transmission, improving anti-malarial strategies in Uganda. Scalability to other countries and diseases looks promising.http://link.springer.com/article/10.1186/s12936-016-1546-5Remote diagnosisMalaria mappingMobile phonesRapid diagnostic tests (RDTs)Process innovationHealthcare |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alberto Larocca Roberto Moro Visconti Michele Marconi |
spellingShingle |
Alberto Larocca Roberto Moro Visconti Michele Marconi Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda Malaria Journal Remote diagnosis Malaria mapping Mobile phones Rapid diagnostic tests (RDTs) Process innovation Healthcare |
author_facet |
Alberto Larocca Roberto Moro Visconti Michele Marconi |
author_sort |
Alberto Larocca |
title |
Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda |
title_short |
Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda |
title_full |
Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda |
title_fullStr |
Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda |
title_full_unstemmed |
Malaria diagnosis and mapping with m-Health and geographic information systems (GIS): evidence from Uganda |
title_sort |
malaria diagnosis and mapping with m-health and geographic information systems (gis): evidence from uganda |
publisher |
BMC |
series |
Malaria Journal |
issn |
1475-2875 |
publishDate |
2016-10-01 |
description |
Abstract Background Rural 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. Methods GIS is used to evaluate the feasibility of m-Health technologies as part of anti-malaria strategies. This study investigates where in Uganda: (1) malaria affects the largest number of people; (2) the application of m-Health protocol based on the mobile network has the highest potential impact. Results About 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. Conclusions The 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-localized data transmission, improving anti-malarial strategies in Uganda. Scalability to other countries and diseases looks promising. |
topic |
Remote diagnosis Malaria mapping Mobile phones Rapid diagnostic tests (RDTs) Process innovation Healthcare |
url |
http://link.springer.com/article/10.1186/s12936-016-1546-5 |
work_keys_str_mv |
AT albertolarocca malariadiagnosisandmappingwithmhealthandgeographicinformationsystemsgisevidencefromuganda AT robertomorovisconti malariadiagnosisandmappingwithmhealthandgeographicinformationsystemsgisevidencefromuganda AT michelemarconi malariadiagnosisandmappingwithmhealthandgeographicinformationsystemsgisevidencefromuganda |
_version_ |
1725258765911982080 |