Abstract
BackgroundUrban 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.MethodsCensus 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.Results4,336 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.ConclusionThis method selected a sample that was simultaneously population-representative and inclusive of important environmental variation. The use of a pseudo-sampling frame and pre-programmed handheld GPS units is more efficient and may yield a more complete sample than traditional methods, and is less expensive than complete population enumeration.
Highlights
Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities
While most Africans still live in rural areas, the proportion of urban dwellers in sub-Saharan Africa (SSA) is significant (35.2% in 2005), and growing at a rate close to double the world average (3.6% versus 2.0%/year from 2000–2005), such that the proportion of Africa's population living in urban areas will exceed 50% by 2030 [3]
Data collection was curtailed for logistical reasons, non-sampled enumeration area (EA) were randomly distributed (Figure 1)
Summary
Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities. Studies attempting to characterize risk factors for urban malaria face many challenges in sampling design, including the lack of preexisting sampling frames, heterogeneity in the distribution of populations, micro-environmental variation, and the spatially focal nature of malaria transmission in cities. In response to these obstacles, researchers have adopted various strategies, including convenience samples from health facilities [7,8,9,10,11,12,13]).) or schools [9,11,14]. These efforts are usually tailored to answer specific questions; for example, the World Health Organization (WHO) rapid urban malaria appraisal (RUMA) methodology uses school and health facility samples to establish an overview of the malaria situation within a defined urban area prior to more detailed research and/or control initiatives [11]
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