MAPPING VECTOR BORNE DISEASE INCIDENCE MODELS FOR PREVENTIVE DECISIONS – CASES FROM CHENNAI CITY, TAMIL NADU INDIA

Abstract submitted to "4th Workshop on Remote Sensing for Developing Countries/GISDECO 8"
MAPPING VECTOR BORNE DISEASE INCIDENCE MODELS FOR PREVENTIVE DECISIONS – CASES FROM CHENNAI CITY, TAMIL NADU INDIA
Environmental Monitoring
S Vincent
University of Madras
S.Sajeevi Prasad
Loyola Institute of Frontier Energy, Loyola College, Chennai
B Balaguru
Scentific Officer, Loyola Institute of Frontier Energy, Loyola College, Chennai 600 034
N Sivagnam
Professor & Head, Department of Geography, University of Madras, Chennai 600 005
B Dhanraj
Senior Entomologist, Health Department,Corporation of Chennai 600 003
Keywords: Vector Borne Diseases,Strom water,Prevalence Model
Presentation preference: oral

Chennai is one of the most important metropolitan cities in India and India’s one of the four metropolitan region and having more than 6.5 million populations. About 800 kms length network of storm water drains in Chennai city depends on the cleanliness, spatial and temporal distribution and intensity of rainfall and urban space usage. The storm water drain system in the city is stagnating throughout year due to the dumping of solid wastes, mixing of sewage water, undulating slopes comparatively equal to sea level and collision of the channels. The stagnation increases perennial mosquito menace besides spread of vector borne diseases such as Malaria and Dengue and recently Chickengunia. Spatial and non spatial information pertaining to the geography of diseases, topography, rainfall and pollution level are required in order to make decisions to prevent the vector born diseases. Geographical Information System (GIS) is useful tool to map vector borne disease incidence/Prevalence. In the present study two zones were selected as study area out of five zones of the Chennai city. Administratively the zones comprise several wards/blocks. The maps of storm water drain were generated from the Municipal Corporation drawings and GPS reading also were noted in all storm water drains and the major waterways. The thematic layers such as Malaria and Dengue prevalence for Ten years, rainfall, Slope, DEM, water samples, water outlets were generated and overlaid in the Map Info GIS domain in order to model the disease incidence and outbreak at the blocks/wards level. The study envisages 7 wards, 4 wards of the zones extremely prevalence to Malaria, Dengue respectively.

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