Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Sociedade Brasileira de Medicina Tropical |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822016000500608 |
Resumo: | Abstract INTRODUCTION: Schistosomiasis is a parasitic infectious disease with a worldwide prevalence. The objective of this work is to identify risk areas for schistosomiasis mansoni transmission in the State of Sergipe, Brazil, during the period from 2005 to 2014. METHODS: We conducted an epidemiological study with secondary data from the Information System Control Program of Schistosomiasis [Sistema de Informação do Programa de Controle da Esquistossomose (SISPCE)]. Temporal trends were analyzed to obtain the annual percentage change (APC) in the rates of annual prevalence. In addition to the description of general indicators of the disease, the spatial analysis was descriptive, by means of the estimator of intensity kernel, and showed spatial dependence by indicators of global Moran (I) and Local Index of Spatial Association (LISA). Thematic maps of spatial distribution were made, identifying priority intervention areas in need of healthcare. RESULTS: There were 78,663 cases of schistosomiasis, with an average of 8.7% positivity recorded; 79.8% of the cases were treated, and Sergipe showed a decreasing positive trend (APC: -2.78). There was the presence of spatial autocorrelation and a significant global Moran index (I = 0.19; p-value = 0.03). We identified clusters of high-risk areas, mainly located in the northeast and southcentral of the state, which each had equally high infection rates. CONCLUSIONS: There was a decreasing positive trend of schistosomiasis in Sergipe. Spatial analysis identified the geographic distribution of risk and allowed the definition of priority areas for the maintenance and intensification of control interventions. |
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Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014SchistosomiasisEpidemiologyGeographical information systemSpatial analysisAbstract INTRODUCTION: Schistosomiasis is a parasitic infectious disease with a worldwide prevalence. The objective of this work is to identify risk areas for schistosomiasis mansoni transmission in the State of Sergipe, Brazil, during the period from 2005 to 2014. METHODS: We conducted an epidemiological study with secondary data from the Information System Control Program of Schistosomiasis [Sistema de Informação do Programa de Controle da Esquistossomose (SISPCE)]. Temporal trends were analyzed to obtain the annual percentage change (APC) in the rates of annual prevalence. In addition to the description of general indicators of the disease, the spatial analysis was descriptive, by means of the estimator of intensity kernel, and showed spatial dependence by indicators of global Moran (I) and Local Index of Spatial Association (LISA). Thematic maps of spatial distribution were made, identifying priority intervention areas in need of healthcare. RESULTS: There were 78,663 cases of schistosomiasis, with an average of 8.7% positivity recorded; 79.8% of the cases were treated, and Sergipe showed a decreasing positive trend (APC: -2.78). There was the presence of spatial autocorrelation and a significant global Moran index (I = 0.19; p-value = 0.03). We identified clusters of high-risk areas, mainly located in the northeast and southcentral of the state, which each had equally high infection rates. CONCLUSIONS: There was a decreasing positive trend of schistosomiasis in Sergipe. Spatial analysis identified the geographic distribution of risk and allowed the definition of priority areas for the maintenance and intensification of control interventions.Sociedade Brasileira de Medicina Tropical - SBMT2016-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822016000500608Revista da Sociedade Brasileira de Medicina Tropical v.49 n.5 2016reponame:Revista da Sociedade Brasileira de Medicina Tropicalinstname:Sociedade Brasileira de Medicina Tropical (SBMT)instacron:SBMT10.1590/0037-8682-0137-2016info:eu-repo/semantics/openAccessSantos,Allan Dantas dosLima,Ana Caroline RodriguesSantos,Márcio BezerraAlves,José Antônio BarretoGóes,Marco Aurélio de OliveiraNunes,Marco Antônio PradoSá,Sidney Lourdes César SouzaAraújo,Karina Conceição Gomes Machado deeng2016-10-31T00:00:00Zoai:scielo:S0037-86822016000500608Revistahttps://www.sbmt.org.br/portal/revista/ONGhttps://old.scielo.br/oai/scielo-oai.php||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br1678-98490037-8682opendoar:2016-10-31T00:00Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT)false |
dc.title.none.fl_str_mv |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
title |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
spellingShingle |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 Santos,Allan Dantas dos Schistosomiasis Epidemiology Geographical information system Spatial analysis |
title_short |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
title_full |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
title_fullStr |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
title_full_unstemmed |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
title_sort |
Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014 |
author |
Santos,Allan Dantas dos |
author_facet |
Santos,Allan Dantas dos Lima,Ana Caroline Rodrigues Santos,Márcio Bezerra Alves,José Antônio Barreto Góes,Marco Aurélio de Oliveira Nunes,Marco Antônio Prado Sá,Sidney Lourdes César Souza Araújo,Karina Conceição Gomes Machado de |
author_role |
author |
author2 |
Lima,Ana Caroline Rodrigues Santos,Márcio Bezerra Alves,José Antônio Barreto Góes,Marco Aurélio de Oliveira Nunes,Marco Antônio Prado Sá,Sidney Lourdes César Souza Araújo,Karina Conceição Gomes Machado de |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Santos,Allan Dantas dos Lima,Ana Caroline Rodrigues Santos,Márcio Bezerra Alves,José Antônio Barreto Góes,Marco Aurélio de Oliveira Nunes,Marco Antônio Prado Sá,Sidney Lourdes César Souza Araújo,Karina Conceição Gomes Machado de |
dc.subject.por.fl_str_mv |
Schistosomiasis Epidemiology Geographical information system Spatial analysis |
topic |
Schistosomiasis Epidemiology Geographical information system Spatial analysis |
description |
Abstract INTRODUCTION: Schistosomiasis is a parasitic infectious disease with a worldwide prevalence. The objective of this work is to identify risk areas for schistosomiasis mansoni transmission in the State of Sergipe, Brazil, during the period from 2005 to 2014. METHODS: We conducted an epidemiological study with secondary data from the Information System Control Program of Schistosomiasis [Sistema de Informação do Programa de Controle da Esquistossomose (SISPCE)]. Temporal trends were analyzed to obtain the annual percentage change (APC) in the rates of annual prevalence. In addition to the description of general indicators of the disease, the spatial analysis was descriptive, by means of the estimator of intensity kernel, and showed spatial dependence by indicators of global Moran (I) and Local Index of Spatial Association (LISA). Thematic maps of spatial distribution were made, identifying priority intervention areas in need of healthcare. RESULTS: There were 78,663 cases of schistosomiasis, with an average of 8.7% positivity recorded; 79.8% of the cases were treated, and Sergipe showed a decreasing positive trend (APC: -2.78). There was the presence of spatial autocorrelation and a significant global Moran index (I = 0.19; p-value = 0.03). We identified clusters of high-risk areas, mainly located in the northeast and southcentral of the state, which each had equally high infection rates. CONCLUSIONS: There was a decreasing positive trend of schistosomiasis in Sergipe. Spatial analysis identified the geographic distribution of risk and allowed the definition of priority areas for the maintenance and intensification of control interventions. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-10-01 |
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=S0037-86822016000500608 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822016000500608 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0037-8682-0137-2016 |
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 |
Sociedade Brasileira de Medicina Tropical - SBMT |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
dc.source.none.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical v.49 n.5 2016 reponame:Revista da Sociedade Brasileira de Medicina Tropical instname:Sociedade Brasileira de Medicina Tropical (SBMT) instacron:SBMT |
instname_str |
Sociedade Brasileira de Medicina Tropical (SBMT) |
instacron_str |
SBMT |
institution |
SBMT |
reponame_str |
Revista da Sociedade Brasileira de Medicina Tropical |
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Revista da Sociedade Brasileira de Medicina Tropical |
repository.name.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT) |
repository.mail.fl_str_mv |
||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br |
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