Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , , , |
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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Memórias do Instituto Oswaldo Cruz |
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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 |
|
_version_ |
1669937712052830208 |