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Geographic Information Systems for the study and control of infectious diseases
A number of papers [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20] discuss the applications of GIS in controlling, monitoring, and surveillance of infectious diseases. However, no research is directed towards a common methodology with special treatment to a disease with respect to GIS application. The present paper is a step towards to find a common method to identify the vulnerable area of infectious disease using GIS.
Methodology
Many factors contribute to the emergence of infectious diseases. Those frequently identified include microbial adaptation and change, human demographics and behavior, environmental changes, technology and economic development, breakdown in public health measures and surveillance, and international travel and commerce. Factors that can influence receptivity include climate and environmental conditions, sanitation, socioeconomic conditions, behavior, nutrition, and genetics. The human population is more vulnerable because of aging, immuno-suppression from medical treatment and disease, the presence of prostheses, exposure to chemicals and environmental pollutants that may act synergistically with microbes to increase the risk of diseases, increased poverty, crowding and stress, increased exposure to UV radiation, and technologic changes. Table 1 lists the different infectious diseases, its Aetiology (cause of disease), epidemiology, and vulnerable group/ conditions. A common methodology could be to develop the related databases regarding climate and environmental conditions, sanitation, socioeconomic conditions, behavior, nutrition, genetics, etc. according to the factors given in column (2). Spatial parameters like environmental conditions, temperature, soil conditions, etc. have to be interpolated using a suitable spatial analytical technique. Column (3) epidemiology provides the information regarding the carriers. The database regarding sanitation, socio-economic, behavior, etc. should be created and related maps should be digitized accordingly. The movements of the carriers should be interpolated, which could be done by using the buffer operations. Last column (4) provides the information about the group, which is vulnerable. These groups/ conditions could be easily identified and can be located on maps/ images. Temporal features like rainfall, low-high temperature, etc, should be identified in regions/ zones. Overlaying these images will give a good picture of the vulnerable area to that disease.
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