However precise geographic data on households are an absolute requirement for critical examination of local variation of the disease and its association with the environment. Household locations can be captured by using GPS (global positioning system) receivers. One way to facilitate the measurement of local variation in health outcomes is to create household-level geographic information systems (GIS) database. Local-level geographic variation of disease obtained from fine resolution geographic data can provide clues about the spatial variability, and may pinpoint areas where health interventions are needed. Regional variation in disease incidence be attributed to regional or global differences in ecological or socio-environmental phenomena. Geographic methods provide a wide spectrum of geographic scales from local to global for analyzing health and health-related data. Such understanding may help the formulation of need based healthcare systems and health intervention programs. By studying disease patterns in space, we can understand the relationships between socioecological exposure and illness. Geographic data are increasingly being employed in health studies. The methodological issues introduced in this paper provide solutions to the technical barriers in constructing household GIS database in a heavily populated urban setting. ![]() The GIS database was then merged with health data, and spatial analysis of health was possible. The use of IKONOS satellite imagery allowed us to construct an accurate household GIS database, which included the size and orientation of the houses. In order to overcome this problem, we used high resolution satellite imagery (IKONOS) to extract relevant geographic information. ![]() We faced this problem when constructing a household GIS database for research sites in Karachi, Pakistan because the sites are comprised of congested groups of multi-storied building and narrow lanes. In some research settings, GPS receivers may fail to capture accurate readings due to structural barriers such as tall buildings. ![]() Household-level geographic information systems (GIS) database are usually constructed using the geographic positioning system (GPS).
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