Using remote, spatial techniques to select a random household sample in a dispersed, semi-nomadic pastoral community: utility for a longitudinal health and demographic surveillance system. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Pearson, Amber; Rzotkiewicz, Amanda; Zwickle, Adam
• Is Part Of: International journal of health geographics. Volume 14:Issue 1(2015)
• Page Start: 1
• Page End: 10
• Publication Date: 2015-12
• Subjects: Google earth -- Random sample -- Transect -- Longitudinal household survey -- Sampling frame; Geographic information systems -- Health aspects -- Periodicals; Geography -- Health aspects -- Periodicals; 614.40285
• DOI: 10.1186/s12942-015-0026-4
• Languages: English
• ISSNs: 1476-072X

Abstract

Abstract Background Obtaining a random household sample can be expensive and challenging. In a dispersed community of semi-nomadic households in rural Tanzania, this study aimed to test an alternative method utilizing freely available aerial imagery. Methods We pinned every single-standing structure orboma (compound) in Naitolia, Tanzania using a 'placemark' in Google Earth Pro (version 7.1.2.2041). Next, a local expert assisted in removing misclassified placemarks. A random sample was then selected using a random number generator. The random sample points were mapped and used by survey enumerators to navigate. Results We created a spatial sample frame and a random sample in 34.5 student working hours, 3 local expert hours and 1.5 academic working hours. Challenges included determining whether homes were occupied or abandoned, developing a protocol for placemark inclusion and quality issues with the aerial imagery itself. In the field, 175 sample points were visited and 170 of these (97 %) were actual households. The primary advantages of this method were the: (a) ability to generate a robust random sample in a rural and remote area; (b) lack of reliance on existing, external population data sources; and (c) relatively low levels of funding and time required. Conclusions This method to develop a spatial sample frame was efficient and cost-effective when compared to in-field generation of a household inventory or GPS tracking of households. Utilizing a local expert to review the sample frame prior to field testing greatly increased accuracy. Overall, this method is a promising alternative to expensive and possibly biased household inventories or in-field GPS data collection for all households.