03104nas a2200337   4500000000100000008004100001653001200042653003100054653003700085653002200122653002600144653001700170100001500187700001500202700001400217700001200231700001600243700001500259700001500274700001300289700001800302700001300320700001500333700001100348245015800359856008700517300000700604490000700611520213400618022001402752       2018                            d10aMhealth10aElectronic data collection10aGeographical information systems10aMobile technology10aParticipatory mapping10aSurveillance1 aFornace KM1 aSurendra H1 aAbidin TR1 aReyes R1 aMacalinao M1 aStresman G1 aLuchavez J1 aAhmad RA1 aSupargiyono S1 aEspino F1 aDrakeley C1 aCook J00aUse of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings.  uhttps://ij-healthgeographics.biomedcentral.com/track/pdf/10.1186/s12942-018-0141-0  a210 v173 a<p><strong>BACKGROUND: </strong>Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.</p>

<p><strong>RESULTS: </strong>Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116&nbsp;m (IQR 42-368) in Rizal and 493&nbsp;m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.</p>

<p><strong>CONCLUSIONS: </strong>Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.</p>
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