Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

International Journal of Health Geographics

Azizur R Molla³  Richard R Rediske²  Peter J Wampler¹ 

[1]Department of Geology, Grand Valley State University, 1 Campus Dr, Allendale, MI 49401, USA

[2]Annis Water Resource Institute, Grand Valley State University, 740 W. Shoreline Drive, Muskegon, MI, 49451, USA

[3]Department of Anthropology, Grand Valley State University, 1 Campus Drive, Allendale, MI, 49401, USA

关键词: GPS;    Anthropology;    Ethnographic study;    Google Earth;    Bacterial water testing;   

Others  :  810271
DOI  :  10.1186/1476-072X-12-3

 received in 2012-11-09, accepted in 2013-01-06,  发布年份 2013

【 摘 要 】

Background

A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner.

Methods

The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households.

Results

A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012.

Conclusions

The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This method provides an important technique that can be applied to other developing countries where a randomized study design is needed but infrastructure is lacking to implement more traditional participant selection methods.

【 授权许可】

   
2013 Wampler et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Lozano-Fuentes S, Elizondo-Quiroga D, Farfan-Ale JA, Loroño-Pino MA, Garcia-Rejon J, Gomez-Carro S, Lira-Zumbardo V, Najera-Vazquez R, Fernandez-Salas I, Calderon-Martinez J: Use of Google EarthTM to strengthen public health capacity and facilitate management of vector-borne diseases in resource-poor environments. Bull World Health Organ 2008, 86:718-725.
• [2]Kleinschmidt I, Omumbo J, Briet O, van de Giesen N, Sogoba N, Mensah NK, Windmeijer P, Moussa M, Teuscher T: An empirical malaria distribution map for West Africa Volume 6. England: Trop Med Int Health; 2001:779-786.
• [3]Carbajo AE, Schweigmann N, Curto SI, de Garin A, Bejaran R: Dengue transmission risk maps of Argentina Volume 6. England: Trop Med Int Health; 2001:170-183.
• [4]Rotela C, Fouque F, Lamfri M, Sabatier P, Introini V, Zaidenberg M, Scavuzzo C: Space-time analysis of the dengue spreading dynamics in the 2004 Tartagal outbreak, Northern Argentina Volume 103. Netherlands: Acta Trop; 2007:1-13.
• [5]Herbreteau V, Salem G, Souris M, Hugot JP, Gonzalez JP: Thirty years of use and improvement of remote sensing, applied to epidemiology: from early promises to lasting frustration Volume 13. England: Health Place; 2007:400-403.
• [6]Mills JW, Curtis A: Geospatial approaches for disease risk communication in marginalized communities Volume 2. United States: Prog Community Health Partnersh; 2008:61-72.
• [7]Boulos MN: Web GIS in practice III: creating a simple interactive map of England's Strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control. Volume 4. England: Int J Health Geogr; 2005:22.
• [8]Kamadjeu R: Tracking the polio virus down the Congo River: a case study on the use of Google Earth in public health planning and mapping Volume 8. England: Int J Health Geogr; 2009:4.
• [9]FERNANDEZ I: Use of Google earth to facilitate GIS based decision support systems for arthropod-borne diseases. Advances in disease surveillance 2007, 4:91-91.
• [10]Chang AY, Parrales ME, Jimenez J, Sobieszczyk ME, Hammer SM, Copenhaver DJ, Kulkarni RP: Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries Volume 8. England: Int J Health Geogr; 2009:49.
• [11]Kun Y, Le-Ping S, Yi-Xin H, Guo-Jing Y, Feng W, De-Rong H, Wei L, Jian-Feng Z, Yong-Sheng L, Xiao-Nong Z: A real-time platform for monitoring schistosomiasis transmission supported by Google Earth and a web-based geographical information system. Geospat Health 2012, 6:195-203.
• [12]Galway LP, Bell N, Al Shatari SAE, Hagopian A, Burnham G, Flaxman A, Weiss WM, Rajaratnam J, Takaro TK: A two-stage cluster sampling method using gridded population data, a GIS, and Google Earth TM imagery in a population-based mortality survey in Iraq. Int J Health Geogr 2012, 11:12. BioMed Central Full Text
• [13]Babbie E: Social Research Counts. Belmont, CA, USA: Wadsworth Cengage Learning; 2012.
• [14]Mann PS: Introductory Statistics. New York, NY, USA: John Wiley & Sons Inc; 2007.
• [15]Hôpital Albert Schweitzer Official Web Site: Hôpital Albert Schweitzer - saving lives, changing lives for more than 50 years. http://www.hashaiti.org/ webcite
• [16]Bertuzzo E, Mari L, Righetto L, Gatto M, Casagrandi R, Blokesch M, Rodriguez-Iturbe I, Rinaldo A: Prediction of the spatial evolution and effects of control measures for the unfolding Haiti cholera outbreak. Geophys Res Lett 2011, 38:L06403.
• [17]Association APH: Water Environment Federation (1998) Standard methods for the examination of water and wastewater. DC: Washington; 1994.
• [18]Earth Explorer. http://earthexplorer.usgs.gov/ webcite