The Geographic Information System applied to study schistosomiasis in Pernambuco
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Saúde Pública |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000100288 |
Resumo: | ABSTRACT OBJECTIVE Diagnose risk environments for schistosomiasis in coastal localities of Pernambuco using geoprocessing techniques. METHODS A coproscopic and malacological survey were carried out in the Forte Orange and Serrambi areas. Environmental variables (temperature, salinity, pH, total dissolved solids and water fecal coliform dosage) were collected from Biomphalaria breeding sites or foci. The spatial analysis was performed using ArcGis 10.1 software, applying the kernel estimator, elevation map, and distance map. RESULTS In Forte Orange, 4.3% of the population had S. mansoni and were found two B. glabrata and 26 B. straminea breeding sites. The breeding sites had temperatures of 25ºC to 41ºC, pH of 6.9 to 11.1, total dissolved solids between 148 and 661, and salinity of 1,000 d. In Serrambi, 4.4% of the population had S. mansoni and were found seven B. straminea and seven B. glabrata breeding sites. Breeding sites had temperatures of 24ºC to 36ºC, pH of 7.1 to 9.8, total dissolved solids between 116 and 855, and salinity of 1,000 d. The kernel estimator shows the clusters of positive patients and foci of Biomphalaria, and the digital elevation map indicates areas of rainwater concentration. The distance map shows the proximity of the snail foci with schools and health facilities. CONCLUSIONS Geoprocessing techniques prove to be a competent tool for locating and scaling the risk areas for schistosomiasis, and can subsidize the health services control actions. |
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Revista de Saúde Pública |
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The Geographic Information System applied to study schistosomiasis in PernambucoSchistosomiasis, epidemiologyBiomphalaria, parasitologyRisk FactorsGeographical Localization of RiskGeographic Information Systems, utilizationABSTRACT OBJECTIVE Diagnose risk environments for schistosomiasis in coastal localities of Pernambuco using geoprocessing techniques. METHODS A coproscopic and malacological survey were carried out in the Forte Orange and Serrambi areas. Environmental variables (temperature, salinity, pH, total dissolved solids and water fecal coliform dosage) were collected from Biomphalaria breeding sites or foci. The spatial analysis was performed using ArcGis 10.1 software, applying the kernel estimator, elevation map, and distance map. RESULTS In Forte Orange, 4.3% of the population had S. mansoni and were found two B. glabrata and 26 B. straminea breeding sites. The breeding sites had temperatures of 25ºC to 41ºC, pH of 6.9 to 11.1, total dissolved solids between 148 and 661, and salinity of 1,000 d. In Serrambi, 4.4% of the population had S. mansoni and were found seven B. straminea and seven B. glabrata breeding sites. Breeding sites had temperatures of 24ºC to 36ºC, pH of 7.1 to 9.8, total dissolved solids between 116 and 855, and salinity of 1,000 d. The kernel estimator shows the clusters of positive patients and foci of Biomphalaria, and the digital elevation map indicates areas of rainwater concentration. The distance map shows the proximity of the snail foci with schools and health facilities. CONCLUSIONS Geoprocessing techniques prove to be a competent tool for locating and scaling the risk areas for schistosomiasis, and can subsidize the health services control actions.Faculdade de Saúde Pública da Universidade de São Paulo2017-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000100288Revista de Saúde Pública v.51 2017reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USP10.11606/s1518-8787.2017051000069info:eu-repo/semantics/openAccessBarbosa,Verônica SantosLoyo,Rodrigo MoraesGuimarães,Ricardo José de Paula Souza eBarbosa,Constança Simõeseng2017-11-14T00:00:00Zoai:scielo:S0034-89102017000100288Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0034-8910&lng=pt&nrm=isoONGhttps://old.scielo.br/oai/scielo-oai.phprevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2017-11-14T00:00Revista de Saúde Pública - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
title |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
spellingShingle |
The Geographic Information System applied to study schistosomiasis in Pernambuco Barbosa,Verônica Santos Schistosomiasis, epidemiology Biomphalaria, parasitology Risk Factors Geographical Localization of Risk Geographic Information Systems, utilization |
title_short |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
title_full |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
title_fullStr |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
title_full_unstemmed |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
title_sort |
The Geographic Information System applied to study schistosomiasis in Pernambuco |
author |
Barbosa,Verônica Santos |
author_facet |
Barbosa,Verônica Santos Loyo,Rodrigo Moraes Guimarães,Ricardo José de Paula Souza e Barbosa,Constança Simões |
author_role |
author |
author2 |
Loyo,Rodrigo Moraes Guimarães,Ricardo José de Paula Souza e Barbosa,Constança Simões |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Barbosa,Verônica Santos Loyo,Rodrigo Moraes Guimarães,Ricardo José de Paula Souza e Barbosa,Constança Simões |
dc.subject.por.fl_str_mv |
Schistosomiasis, epidemiology Biomphalaria, parasitology Risk Factors Geographical Localization of Risk Geographic Information Systems, utilization |
topic |
Schistosomiasis, epidemiology Biomphalaria, parasitology Risk Factors Geographical Localization of Risk Geographic Information Systems, utilization |
description |
ABSTRACT OBJECTIVE Diagnose risk environments for schistosomiasis in coastal localities of Pernambuco using geoprocessing techniques. METHODS A coproscopic and malacological survey were carried out in the Forte Orange and Serrambi areas. Environmental variables (temperature, salinity, pH, total dissolved solids and water fecal coliform dosage) were collected from Biomphalaria breeding sites or foci. The spatial analysis was performed using ArcGis 10.1 software, applying the kernel estimator, elevation map, and distance map. RESULTS In Forte Orange, 4.3% of the population had S. mansoni and were found two B. glabrata and 26 B. straminea breeding sites. The breeding sites had temperatures of 25ºC to 41ºC, pH of 6.9 to 11.1, total dissolved solids between 148 and 661, and salinity of 1,000 d. In Serrambi, 4.4% of the population had S. mansoni and were found seven B. straminea and seven B. glabrata breeding sites. Breeding sites had temperatures of 24ºC to 36ºC, pH of 7.1 to 9.8, total dissolved solids between 116 and 855, and salinity of 1,000 d. The kernel estimator shows the clusters of positive patients and foci of Biomphalaria, and the digital elevation map indicates areas of rainwater concentration. The distance map shows the proximity of the snail foci with schools and health facilities. CONCLUSIONS Geoprocessing techniques prove to be a competent tool for locating and scaling the risk areas for schistosomiasis, and can subsidize the health services control actions. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 |
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://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000100288 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000100288 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.11606/s1518-8787.2017051000069 |
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 |
Faculdade de Saúde Pública da Universidade de São Paulo |
publisher.none.fl_str_mv |
Faculdade de Saúde Pública da Universidade de São Paulo |
dc.source.none.fl_str_mv |
Revista de Saúde Pública v.51 2017 reponame:Revista de Saúde Pública instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Revista de Saúde Pública |
collection |
Revista de Saúde Pública |
repository.name.fl_str_mv |
Revista de Saúde Pública - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
revsp@org.usp.br||revsp1@usp.br |
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1748936504228446208 |