Int J Health Geogr - Leveraging community health worker system to map a mountainous rural district in low resource setting: a low-cost approach to expand use of geographic information systems for public health.


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CKGROUND: Geographic Information Systems (GIS) have become an important tool in monitoring and improving health services, particularly at local levels. However, GIS data are often unavailable in rural settings and village-level mapping is resource-intensive. This study describes the use of community health workers' (CHW) supervisors to map villages in a mountainous rural district of Northern Rwanda and subsequent use of these data to map village-level variability in safe water availability.METHODS: We developed a low literacy and skills-focused training in the local language (Kinyarwanda) to train 86 CHW Supervisors and 25 nurses in charge of community health at the health center (HC) and health post (HP) levels to collect the geographic coordinates of the villages using Global Positioning Systems (GPS). Data were validated through meetings with key stakeholders at the sub-district and district levels and joined using ArcMap 10 Geo-processing tools. Costs were calculated using program budgets and activities' records, and compared with the estimated costs of mapping using a separate, trained GIS team. To demonstrate the usefulness of this work, we mapped drinking water sources (DWS) from data collected by CHW supervisors from the chief of the village. DWSs were categorized as safe versus unsafe using World Health Organization definitions.RESULT: Following training, each CHW Supervisor spent five days collecting data on the villages in their coverage area. Over 12?months, the CHW supervisors mapped the district's 573 villages using 12 shared GPS devices. Sector maps were produced and distributed to local officials. The cost of mapping using CHW supervisors was $29,692, about two times less than the estimated cost of mapping using a trained and dedicated GIS team ($60,112). The availability of local mapping was able to rapidly identify village-level disparities in DWS, with lower access in populations living near to lakes and wetlands (p<.001).CONCLUSION: Existing national CHW system can be leveraged to inexpensively and rapidly map villages even in mountainous rural areas. These data are important to provide managers and decision makers with local-level GIS data to rapidly identify variability in health and other related services to better target and evaluate interventions.

Resumo Limpo

ckground geograph inform system gis becom import tool monitor improv health servic particular local level howev gis data often unavail rural set villagelevel map resourceintens studi describ use communiti health worker chw supervisor map villag mountain rural district northern rwanda subsequ use data map villagelevel variabl safe water availabilitymethod develop low literaci skillsfocus train local languag kinyarwanda train chw supervisor nurs charg communiti health health center hc health post hp level collect geograph coordin villag use global posit system gps data valid meet key stakehold subdistrict district level join use arcmap geoprocess tool cost calcul use program budget activ record compar estim cost map use separ train gis team demonstr use work map drink water sourc dws data collect chw supervisor chief villag dwss categor safe versus unsaf use world health organ definitionsresult follow train chw supervisor spent five day collect data villag coverag area month chw supervisor map district villag use share gps devic sector map produc distribut local offici cost map use chw supervisor two time less estim cost map use train dedic gis team avail local map abl rapid identifi villagelevel dispar dws lower access popul live near lake wetland pconclus exist nation chw system can leverag inexpens rapid map villag even mountain rural area data import provid manag decis maker locallevel gis data rapid identifi variabl health relat servic better target evalu intervent

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