A random spatial sampling method in a rural developing nation

BMC Public Health

Charles C Branas¹  Frances K Barg²  Kent DW Bream²  Michelle C Kondo¹ 

[1]Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA 19104-6021, USA

[2]Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, 141-2 Anatomy and Chemistry, 3620 Hamilton Walk, Philadelphia, PA 19104, USA

关键词: Guatemala;    Satellite imagery;    Global positioning system (GPS);    Geographic information system (GIS);    Social surveys;    Geographic random sampling;   

Others  :  1131583
DOI  :  10.1186/1471-2458-14-338

 received in 2013-10-11, accepted in 2014-04-04,  发布年份 2014

【 摘 要 】

Background

Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population.

Methods

We describe a stratified random sampling method using geographical information system (GIS) software and global positioning system (GPS) technology for application in a health survey in a rural region of Guatemala, as well as a qualitative study of the enumeration process.

Results

This method offers an alternative sampling technique that could reduce opportunities for bias in household selection compared to cluster methods. However, its use is subject to issues surrounding survey preparation, technological limitations and in-the-field household selection. Application of this method in remote areas will raise challenges surrounding the boundary delineation process, use and translation of satellite imagery between GIS and GPS, and household selection at each survey point in varying field conditions. This method favors household selection in denser urban areas and in new residential developments.

Conclusions

Random spatial sampling methodology can be used to survey a random sample of population in a remote region of a developing nation. Although this method should be further validated and compared with more established methods to determine its utility in social survey applications, it shows promise for use in developing nations with resource-challenged environments where detailed geographic and human census data are less available.

【 授权许可】

   
2014 Kondo et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Levy PS, Lemeshow S: Sampling of Populations: Methods and Applications. New York: Wiley; 1991.
• [2]Bostoen K, Bilukha OO, Fenn B, Morgan OW, Tam CC, Veen A, Checchi F: Methods for health surveys in difficult settings: charting progress, moving forward. Emerg Themes Epidemiol 2007, 4:13. BioMed Central Full Text
• [3]Siri JG, Lindblade KA, Rosen DH, Onyango B, Vulule JM, Slutsker L, Wilson ML: A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology. Malar J 2008, 7:315.
• [4]Kolbe AR, Hutson RA: Human rights abuse and other criminal violations in Port-au-Prince, Haiti: a random survey of households. Lancet 2006, 368:864-873.
• [5]World Health Organization: Training for Mid-Level Managers: The EPI Coverage Survey. Geneva: WHO Expanded Programme on Immunization; 1991.
• [6]Roberts L, Despines M: Mortality in the Democratic Republic of the Congo. Lancet 1999, 353:2249-2250.
• [7]Grandesso F, Sanderson F, Kruijt J, Koene T, Brown V: Mortality and malnutrition among populations living in South Darfur, Sudan: results of 3 surveys, September 2004. JAMA 2005, 293:1490-1494.
• [8]Grais RF, Rose AMC, Guthmann J-P: Don’t spin the pen: two alternative methods for second-stage sampling in urban cluster surveys. Emerg Themes Epidemiol 2007, 4:8. BioMed Central Full Text
• [9]Brogan D, Flagg EW, Deming M, Waldman R: Increasing the accuracy of the expanded programme on immunization’s cluster survey design. Ann Epidemiol 1994, 4:302-311.
• [10]Lemeshow S, Tserkovnyi AG, Tulloch JL, Dowd JE, Lwanga SK, Keja J: A computer simulation of the EPI survey strategy. Int J Epidemiol 1985, 14:473-481.
• [11]Turner AG, Magnani RJ, Shuaib M: A not quite as quick but much cleaner alternative to the Expanded Programme on Immunization (EPI) cluster survey design. Int J Epidemiol 1996, 25:198-203.
• [12]Berry BJ, Baker AM: Geographic sampling. In Spatial Analysis. Edited by Berry BJ, Marble DF. Englewood Cliffs: NJ: Prentice-Hall; 1968:91-100.
• [13]Caeiro S, Painho M, Goovaerts P, Costa H, Sousa S: Spatial sampling design for sediment quality assessment in estuaries. Environ Model Softw 2003, 18:853-859.
• [14]Williams MS: New approach to areal sampling in ecological surveys. For Ecol Manag 2001, 154:11-22.
• [15]Kumar N: Spatial sampling design for a demographic and health survey. Popul Res Policy Rev 2007, 26:581-599.
• [16]Kondo MC, Rivera R, Rullman S Jr: Protecting the idyll but not the environment: second homes, amenity migration and rural exclusion in Washington State. Landsc Urban Plan 2012, 106:174-182.
• [17]Kolbe AR, Hutson RA, Shannon H, Trzcinski E, Miles B, Levitz N, Puccio M, James L, Noel JR, Muggah R: Mortality, crime and access to basic needs before and after the Haiti earthquake: a random survey of Port-au-Prince households. Med Confl Surviv 2010, 26:281-297.
• [18]Shannon H, Hutson R, Kolbe A, Stringer B, Haines T: Choosing a survey sample when data on the population are limited: a method using global positioning systems and aerial and satellite photographs. Emerg Themes Epidemiol 2012, 9:5. BioMed Central Full Text
• [19]Bose SK, Bream KDW, Barg FK, Band RA: Willingness to pay for emergency referral transport in a developing setting: a geographically randomized study. Acad Emerg Med 2012, 19:793-800.
• [20]Kaiser R, Spiegel PB, Henderson AK, Gerber ML: The application of geographic information systems and global positioning systems in humanitarian emergencies: lessons learned, programme implications and future research. Disasters 2003, 27:127-140.
• [21]Municipio de Santiago Atitlán: Plan de Desarrollo Municipal, Municipio de Santiago Atitlán. 2010.
• [22]Nagata JM, Valeggia CR, Barg FK, Bream KDW: Body mass index, socio-economic status and socio-behavioral practices among Tz’utujil Maya women. Econ Hum Biol 2009, 7:96-106.