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

Detalhes bibliográficos
Autor(a) principal: Bhunia,Gouri Sankar
Data de Publicação: 2012
Outros Autores: Chatterjee,Nandini, Kumar,Vijay, Siddiqui,Niyamat Ali, Mandal,Rakesh, Das,Pradeep, Kesari,Shreekant
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Memórias do Instituto Oswaldo Cruz
Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762012000500007
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.
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spelling Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approachkala-azarGISNDVIwetness indexgeo-environmental risk modelRemote 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.Instituto Oswaldo Cruz, Ministério da Saúde2012-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762012000500007Memórias do Instituto Oswaldo Cruz v.107 n.5 2012reponame:Memórias do Instituto Oswaldo Cruzinstname:Fundação Oswaldo Cruzinstacron:FIOCRUZ10.1590/S0074-02762012000500007info:eu-repo/semantics/openAccessBhunia,Gouri SankarChatterjee,NandiniKumar,VijaySiddiqui,Niyamat AliMandal,RakeshDas,PradeepKesari,Shreekanteng2020-04-25T17:51:13Zhttp://www.scielo.br/oai/scielo-oai.php0074-02761678-8060opendoar:null2020-04-26 02:18:25.094Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruztrue
dc.title.none.fl_str_mv Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
title Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
spellingShingle Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
Bhunia,Gouri Sankar
kala-azar
GIS
NDVI
wetness index
geo-environmental risk model
title_short Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
title_full Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
title_fullStr Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
title_full_unstemmed Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
title_sort Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
author Bhunia,Gouri Sankar
author_facet Bhunia,Gouri Sankar
Chatterjee,Nandini
Kumar,Vijay
Siddiqui,Niyamat Ali
Mandal,Rakesh
Das,Pradeep
Kesari,Shreekant
author_role author
author2 Chatterjee,Nandini
Kumar,Vijay
Siddiqui,Niyamat Ali
Mandal,Rakesh
Das,Pradeep
Kesari,Shreekant
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Bhunia,Gouri Sankar
Chatterjee,Nandini
Kumar,Vijay
Siddiqui,Niyamat Ali
Mandal,Rakesh
Das,Pradeep
Kesari,Shreekant
dc.subject.por.fl_str_mv kala-azar
GIS
NDVI
wetness index
geo-environmental risk model
topic kala-azar
GIS
NDVI
wetness index
geo-environmental risk model
dc.description.none.fl_txt_mv 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.
description 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.
publishDate 2012
dc.date.none.fl_str_mv 2012-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762012000500007
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762012000500007
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0074-02762012000500007
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto Oswaldo Cruz, Ministério da Saúde
publisher.none.fl_str_mv Instituto Oswaldo Cruz, Ministério da Saúde
dc.source.none.fl_str_mv Memórias do Instituto Oswaldo Cruz v.107 n.5 2012
reponame:Memórias do Instituto Oswaldo Cruz
instname:Fundação Oswaldo Cruz
instacron:FIOCRUZ
reponame_str Memórias do Instituto Oswaldo Cruz
collection Memórias do Instituto Oswaldo Cruz
instname_str Fundação Oswaldo Cruz
instacron_str FIOCRUZ
institution FIOCRUZ
repository.name.fl_str_mv Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruz
repository.mail.fl_str_mv
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