Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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=S0034-89102016000100215 |
Resumo: | ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care. |
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Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)Tuberculosis, epidemiologyHospitalizationSpatial AnalysisGeographic Information SystemsEcological StudiesABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.Faculdade de Saúde Pública da Universidade de São Paulo2016-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102016000100215Revista de Saúde Pública v.50 2016reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USP10.1590/S1518-8787.2016050006049info:eu-repo/semantics/openAccessYamamura,MellinaFreitas,Isabela Moreira deSanto Neto,MarcelinoChiaravalloti Neto,FranciscoPopolin,Marcela Antunes PaschoalArroyo,Luiz HenriqueRodrigues,Ludmila Barbosa BandeiraCrispim,Juliane AlmeidaArcêncio,Ricardo Alexandreeng2016-05-09T00:00:00Zoai:scielo:S0034-89102016000100215Revistahttp://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:2016-05-09T00:00Revista de Saúde Pública - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
title |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
spellingShingle |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) Yamamura,Mellina Tuberculosis, epidemiology Hospitalization Spatial Analysis Geographic Information Systems Ecological Studies |
title_short |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
title_full |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
title_fullStr |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
title_full_unstemmed |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
title_sort |
Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) |
author |
Yamamura,Mellina |
author_facet |
Yamamura,Mellina Freitas,Isabela Moreira de Santo Neto,Marcelino Chiaravalloti Neto,Francisco Popolin,Marcela Antunes Paschoal Arroyo,Luiz Henrique Rodrigues,Ludmila Barbosa Bandeira Crispim,Juliane Almeida Arcêncio,Ricardo Alexandre |
author_role |
author |
author2 |
Freitas,Isabela Moreira de Santo Neto,Marcelino Chiaravalloti Neto,Francisco Popolin,Marcela Antunes Paschoal Arroyo,Luiz Henrique Rodrigues,Ludmila Barbosa Bandeira Crispim,Juliane Almeida Arcêncio,Ricardo Alexandre |
author2_role |
author author author author author author author author |
dc.contributor.author.fl_str_mv |
Yamamura,Mellina Freitas,Isabela Moreira de Santo Neto,Marcelino Chiaravalloti Neto,Francisco Popolin,Marcela Antunes Paschoal Arroyo,Luiz Henrique Rodrigues,Ludmila Barbosa Bandeira Crispim,Juliane Almeida Arcêncio,Ricardo Alexandre |
dc.subject.por.fl_str_mv |
Tuberculosis, epidemiology Hospitalization Spatial Analysis Geographic Information Systems Ecological Studies |
topic |
Tuberculosis, epidemiology Hospitalization Spatial Analysis Geographic Information Systems Ecological Studies |
description |
ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01 |
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=S0034-89102016000100215 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102016000100215 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1518-8787.2016050006049 |
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.50 2016 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 |
_version_ |
1748936503348690944 |