Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach


Autoria(s): Bhunia,Gouri Sankar; Chatterjee,Nandini; Kumar,Vijay; Siddiqui,Niyamat Ali; Mandal,Rakesh; Das,Pradeep; Kesari,Shreekant
Data(s)

01/08/2012

Resumo

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.

Formato

text/html

Identificador

http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762012000500007

Idioma(s)

en

Publicador

Instituto Oswaldo Cruz, Ministério da Saúde

Fonte

Memórias do Instituto Oswaldo Cruz v.107 n.5 2012

Palavras-Chave #kala-azar #GIS #NDVI #wetness index #geo-environmental risk model
Tipo

journal article