A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology
Abstract Background Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities. A novel sampling strategy was developed for urban areas to generate a sample simultaneously representative of population and inhabited environments. S...
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ftdoajarticles:oai:doaj.org/article:d415292d6cde4c01ba24fa8cdd02aaee 2023-05-15T15:14:07+02:00 A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology Slutsker Laurence Vulule John M Onyango Bernard Rosen Daniel H Lindblade Kim A Siri Jose G Wilson Mark L 2008-02-01T00:00:00Z https://doi.org/10.1186/1475-2875-7-39 https://doaj.org/article/d415292d6cde4c01ba24fa8cdd02aaee EN eng BMC http://www.malariajournal.com/content/7/1/39 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-7-39 1475-2875 https://doaj.org/article/d415292d6cde4c01ba24fa8cdd02aaee Malaria Journal, Vol 7, Iss 1, p 39 (2008) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2008 ftdoajarticles https://doi.org/10.1186/1475-2875-7-39 2022-12-31T04:49:46Z Abstract Background Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities. A novel sampling strategy was developed for urban areas to generate a sample simultaneously representative of population and inhabited environments. Such a strategy should facilitate analysis of important epidemiological relationships in this ecological context. Methods Census maps and summary data for Kisumu, Kenya, were used to create a pseudo-sampling frame using the geographic coordinates of census-sampled structures. For every enumeration area (EA) designated as urban by the census (n = 535), a sample of structures equal to one-tenth the number of households was selected. In EAs designated as rural (n = 32), a geographically random sample totalling one-tenth the number of households was selected from a grid of points at 100 m intervals. The selected samples were cross-referenced to a geographic information system, and coordinates transferred to handheld global positioning units. Interviewers found the closest eligible household to the sampling point and interviewed the caregiver of a child aged < 10 years. The demographics of the selected sample were compared with results from the Kenya Demographic and Health Survey to assess sample validity. Results were also compared among urban and rural EAs. Results 4,336 interviews were completed in 473 of the 567 study area EAs from June 2002 through February 2003. EAs without completed interviews were randomly distributed, and non-response was approximately 2%. Mean distance from the assigned sampling point to the completed interview was 74.6 m, and was significantly less in urban than rural EAs, even when controlling for number of households. The selected sample had significantly more children and females of childbearing age than the general population, and fewer older individuals. Conclusion This method selected a sample that was simultaneously population-representative and inclusive of important environmental ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 7 1 39 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Slutsker Laurence Vulule John M Onyango Bernard Rosen Daniel H Lindblade Kim A Siri Jose G Wilson Mark L A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities. A novel sampling strategy was developed for urban areas to generate a sample simultaneously representative of population and inhabited environments. Such a strategy should facilitate analysis of important epidemiological relationships in this ecological context. Methods Census maps and summary data for Kisumu, Kenya, were used to create a pseudo-sampling frame using the geographic coordinates of census-sampled structures. For every enumeration area (EA) designated as urban by the census (n = 535), a sample of structures equal to one-tenth the number of households was selected. In EAs designated as rural (n = 32), a geographically random sample totalling one-tenth the number of households was selected from a grid of points at 100 m intervals. The selected samples were cross-referenced to a geographic information system, and coordinates transferred to handheld global positioning units. Interviewers found the closest eligible household to the sampling point and interviewed the caregiver of a child aged < 10 years. The demographics of the selected sample were compared with results from the Kenya Demographic and Health Survey to assess sample validity. Results were also compared among urban and rural EAs. Results 4,336 interviews were completed in 473 of the 567 study area EAs from June 2002 through February 2003. EAs without completed interviews were randomly distributed, and non-response was approximately 2%. Mean distance from the assigned sampling point to the completed interview was 74.6 m, and was significantly less in urban than rural EAs, even when controlling for number of households. The selected sample had significantly more children and females of childbearing age than the general population, and fewer older individuals. Conclusion This method selected a sample that was simultaneously population-representative and inclusive of important environmental ... |
format |
Article in Journal/Newspaper |
author |
Slutsker Laurence Vulule John M Onyango Bernard Rosen Daniel H Lindblade Kim A Siri Jose G Wilson Mark L |
author_facet |
Slutsker Laurence Vulule John M Onyango Bernard Rosen Daniel H Lindblade Kim A Siri Jose G Wilson Mark L |
author_sort |
Slutsker Laurence |
title |
A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
title_short |
A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
title_full |
A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
title_fullStr |
A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
title_full_unstemmed |
A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
title_sort |
census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology |
publisher |
BMC |
publishDate |
2008 |
url |
https://doi.org/10.1186/1475-2875-7-39 https://doaj.org/article/d415292d6cde4c01ba24fa8cdd02aaee |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 7, Iss 1, p 39 (2008) |
op_relation |
http://www.malariajournal.com/content/7/1/39 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-7-39 1475-2875 https://doaj.org/article/d415292d6cde4c01ba24fa8cdd02aaee |
op_doi |
https://doi.org/10.1186/1475-2875-7-39 |
container_title |
Malaria Journal |
container_volume |
7 |
container_issue |
1 |
container_start_page |
39 |
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1766344607797346304 |