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Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)

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 consi...

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Autores principales: Yamamura, Mellina, de Freitas, Isabela Moreira, Santo, Marcelino, Chiaravalloti, Francisco, Popolin, Marcela Antunes Paschoal, Arroyo, Luiz Henrique, Rodrigues, Ludmila Barbosa Bandeira, Crispim, Juliane Almeida, Arcêncio, Ricardo Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Saúde Pública da Universidade de São Paulo 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902087/
https://www.ncbi.nlm.nih.gov/pubmed/27191156
http://dx.doi.org/10.1590/S1518-8787.2016050006049
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author Yamamura, Mellina
de Freitas, Isabela Moreira
Santo, Marcelino
Chiaravalloti, Francisco
Popolin, Marcela Antunes Paschoal
Arroyo, Luiz Henrique
Rodrigues, Ludmila Barbosa Bandeira
Crispim, Juliane Almeida
Arcêncio, Ricardo Alexandre
author_facet Yamamura, Mellina
de Freitas, Isabela Moreira
Santo, Marcelino
Chiaravalloti, Francisco
Popolin, Marcela Antunes Paschoal
Arroyo, Luiz Henrique
Rodrigues, Ludmila Barbosa Bandeira
Crispim, Juliane Almeida
Arcêncio, Ricardo Alexandre
author_sort Yamamura, Mellina
collection PubMed
description 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 SaTScan(TM) 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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spelling pubmed-49020872016-06-21 Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) Yamamura, Mellina de Freitas, Isabela Moreira Santo, Marcelino Chiaravalloti, Francisco Popolin, Marcela Antunes Paschoal Arroyo, Luiz Henrique Rodrigues, Ludmila Barbosa Bandeira Crispim, Juliane Almeida Arcêncio, Ricardo Alexandre Rev Saude Publica Original Article 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 SaTScan(TM) 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 Paulo 2016-04-27 /pmc/articles/PMC4902087/ /pubmed/27191156 http://dx.doi.org/10.1590/S1518-8787.2016050006049 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Yamamura, Mellina
de Freitas, Isabela Moreira
Santo, Marcelino
Chiaravalloti, Francisco
Popolin, Marcela Antunes Paschoal
Arroyo, Luiz Henrique
Rodrigues, Ludmila Barbosa Bandeira
Crispim, Juliane Almeida
Arcêncio, Ricardo Alexandre
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)
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_short 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)
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902087/
https://www.ncbi.nlm.nih.gov/pubmed/27191156
http://dx.doi.org/10.1590/S1518-8787.2016050006049
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