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Memórias do Instituto Oswaldo Cruz
Fundação Oswaldo Cruz, Fiocruz
ISSN: 1678-8060
EISSN: 1678-8060
Vol. 107, No. 5, 2012, pp. 609-620
Bioline Code: oc12096
Full paper language: English
Document type: Research Article
Document available free of charge

Memórias do Instituto Oswaldo Cruz, Vol. 107, No. 5, 2012, pp. 609-620

 en Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
Bhunia, Gouri Sankar; Chatterjee, Nandini; Kumar, Vijay; Siddiqui, Niyamat Ali; Mandal, Rakesh; Das, Pradeep & Kesari, Shreekant


Remote sensing and geographical information technologies were used to discriminate areas of high and low risk for contracting kala-azar or visceral leishmaniasis. Satellite data were digitally processed to generate maps of land cover and spectral indices, such as the normalised difference vegetation index and wetness index. To map estimated vector abundance and indoor climate data, local polynomial interpolations were used based on the weightage values. Attribute layers were prepared based on illiteracy and the unemployed proportion of the population and associated with village boundaries. Pearson’s correlation coefficient was used to estimate the relationship between environmental variables and disease incidence across the study area. The cell values for each input raster in the analysis were assigned values from the evaluation scale. Simple weighting/ratings based on the degree of favourable conditions for kala-azar transmission were used for all the variables, leading to geo-environmental risk model. Variables such as, land use/land cover, vegetation conditions, surface dampness, the indoor climate, illiteracy rates and the size of the unemployed population were considered for inclusion in the geo-environmental kala-azar risk model. The risk model was stratified into areas of “risk” and “non-risk” for the disease, based on calculation of risk indices. The described approach constitutes a promising tool for microlevel kala-azar surveillance and aids in directing control efforts.

kala-azar - GIS - NDVI - wetness index - geo-environmental risk model

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