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See detailIdentifying environmental risk factors for endemic cholera: a raster GIS approach
Ali, M.; Emch, M.; Donnay, Jean-Paul ULg et al

in Health & Place (2002), 8(3), 201-210

The bacteria that cause cholera are known to be normal inhabitants of surface water, however, the environmental risk factors for different biotypes of cholera are not well understood. This study ... [more ▼]

The bacteria that cause cholera are known to be normal inhabitants of surface water, however, the environmental risk factors for different biotypes of cholera are not well understood. This study identifies environmental risk factors for cholera in an endemic area of Bangladesh using a geographic information systems (GIS) approach. The study data were collected from a longitudinal health and demographic surveillance system and the data were integrated within a geographic information system database of the research area. Two study periods were chosen because they had different dominant biotypes of the disease. From 1992 to 1996 El Tor cholera was dominant and from 1983 to 1987 classical cholera was dominant. The study found the same three risk factors for the two biotypes of cholera including proximity to surface water, high population density, and poor educational level. The GIS database was used to measure the risk factors and spatial filtering techniques were employed. These robust spatial methods are offered as an example for future epidemiological research efforts that define environmental risk factors for infectious diseases. (C) 2002 Elsevier Science Ltd. All rights reserved. [less ▲]

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See detailSpatial filtering using a raster geographic information system: methods for scaling health and environmental data
Ali, M.; Emch, M.; Donnay, Jean-Paul ULg

in Health & Place (2002), 8(2), 85-92

Despite the use of geographic information systems (GIS) in academic research, it is still uncommon for public health officials to use such tools for addressing health and environmental issues ... [more ▼]

Despite the use of geographic information systems (GIS) in academic research, it is still uncommon for public health officials to use such tools for addressing health and environmental issues. Complexities in methodological issues for addressing relationships between health and environment, investigating spatial variation of disease, and addressing spatial demand and supply of health care service, hinder the use of GIS in the health sector. This paper demonstrates simple spatial filtering methods for analyzing health and environmental data using a raster GIS. Computing spatial moving average rates reduces individual affects and creates a continuous surface of phenomena. Another spatial analytical method discussed is computation of exposure status surfaces including neighbors' influences weighted by distance decay. These methods describe how health and environmental data can be scaled in order to better address health problems. Spatial filtering methods are demonstrated using health and population surveillance data within a GIS that were collected for approximately 210,000 people in Matlab, Bangladesh. (C) 2002 Published by Elsevier Science Ltd. [less ▲]

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