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Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system

BACKGROUND: We identified dengue transmission areas by using the Geographic Information Systems located at local surveillance units of the Itaboraí municipality in state of Rio de Janeiro. We considered the association among the house infestation index, the disease incidence, and sociodemographic in...

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Autores principales: Vargas, Waldemir Paixão, Kawa, Hélia, Sabroza, Paulo Chagastelles, Soares, Valdenir Bandeira, Honório, Nildimar Alves, de Almeida, Andréa Sobral
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526415/
https://www.ncbi.nlm.nih.gov/pubmed/26243266
http://dx.doi.org/10.1186/s12889-015-2097-3
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author Vargas, Waldemir Paixão
Kawa, Hélia
Sabroza, Paulo Chagastelles
Soares, Valdenir Bandeira
Honório, Nildimar Alves
de Almeida, Andréa Sobral
author_facet Vargas, Waldemir Paixão
Kawa, Hélia
Sabroza, Paulo Chagastelles
Soares, Valdenir Bandeira
Honório, Nildimar Alves
de Almeida, Andréa Sobral
author_sort Vargas, Waldemir Paixão
collection PubMed
description BACKGROUND: We identified dengue transmission areas by using the Geographic Information Systems located at local surveillance units of the Itaboraí municipality in state of Rio de Janeiro. We considered the association among the house infestation index, the disease incidence, and sociodemographic indicators during a prominent dengue outbreak in 2007 and 2008. METHODS: In this ecological study, the Local Surveillance Units (UVLs) of the municipality were used as spatial pattern units. For the house analysis, we used the period of higher vector density that occurred previous to the larger magnitude epidemic range of dengue cases. The average dengue incidence rates calculated in this epidemic range were smoothed using the Bayesian method. The associations among the House Infestation Index (HI), the Bayesian rate of the average dengue incidence, and the sociodemographic indicators were evaluated using a Pearson’s correlation coefficient. The areas that were at a higher risk of dengue occurrence were detected using a kernel density estimation with the kernel quartic function. RESULTS: The dengue transmission pattern in Itaboraí showed that the increase in the vector density preceded the increase in incidence. The HI was positively correlated to the Bayesian dengue incidence rate (r = 0.641; p = 0.01). The higher risk areas were those that were close to the main highways. In the Kernel density estimation analysis, we observed that the regions that were at a higher risk of dengue were those that were located in the UVLs and had the highest population densities; these locations were typically located along major highways. Four nuclei were identified as epicenters of high risk. CONCLUSIONS: The spatial analysis units used in this research, i.e., UVLs, served as a methodological resource for examining the compatibility of different information sources concerning the disease, the vector indices, and the municipal sociodemographic aspects and were arranged in distinct cartographic bases. Dengue is a multi-scale geographic phenomenon, and using the UVLs as analysis units made it possible to differentiate the dengue occurrence throughout the municipality. The methodological approach used in this research helped improve the Itaboraí municipality monitoring activities and the local territorial monitoring in other municipalities that are affected by this public health issue.
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spelling pubmed-45264152015-08-07 Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system Vargas, Waldemir Paixão Kawa, Hélia Sabroza, Paulo Chagastelles Soares, Valdenir Bandeira Honório, Nildimar Alves de Almeida, Andréa Sobral BMC Public Health Research Article BACKGROUND: We identified dengue transmission areas by using the Geographic Information Systems located at local surveillance units of the Itaboraí municipality in state of Rio de Janeiro. We considered the association among the house infestation index, the disease incidence, and sociodemographic indicators during a prominent dengue outbreak in 2007 and 2008. METHODS: In this ecological study, the Local Surveillance Units (UVLs) of the municipality were used as spatial pattern units. For the house analysis, we used the period of higher vector density that occurred previous to the larger magnitude epidemic range of dengue cases. The average dengue incidence rates calculated in this epidemic range were smoothed using the Bayesian method. The associations among the House Infestation Index (HI), the Bayesian rate of the average dengue incidence, and the sociodemographic indicators were evaluated using a Pearson’s correlation coefficient. The areas that were at a higher risk of dengue occurrence were detected using a kernel density estimation with the kernel quartic function. RESULTS: The dengue transmission pattern in Itaboraí showed that the increase in the vector density preceded the increase in incidence. The HI was positively correlated to the Bayesian dengue incidence rate (r = 0.641; p = 0.01). The higher risk areas were those that were close to the main highways. In the Kernel density estimation analysis, we observed that the regions that were at a higher risk of dengue were those that were located in the UVLs and had the highest population densities; these locations were typically located along major highways. Four nuclei were identified as epicenters of high risk. CONCLUSIONS: The spatial analysis units used in this research, i.e., UVLs, served as a methodological resource for examining the compatibility of different information sources concerning the disease, the vector indices, and the municipal sociodemographic aspects and were arranged in distinct cartographic bases. Dengue is a multi-scale geographic phenomenon, and using the UVLs as analysis units made it possible to differentiate the dengue occurrence throughout the municipality. The methodological approach used in this research helped improve the Itaboraí municipality monitoring activities and the local territorial monitoring in other municipalities that are affected by this public health issue. BioMed Central 2015-08-05 /pmc/articles/PMC4526415/ /pubmed/26243266 http://dx.doi.org/10.1186/s12889-015-2097-3 Text en © Vargas et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Vargas, Waldemir Paixão
Kawa, Hélia
Sabroza, Paulo Chagastelles
Soares, Valdenir Bandeira
Honório, Nildimar Alves
de Almeida, Andréa Sobral
Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title_full Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title_fullStr Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title_full_unstemmed Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title_short Association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
title_sort association among house infestation index, dengue incidence, and sociodemographic indicators: surveillance using geographic information system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526415/
https://www.ncbi.nlm.nih.gov/pubmed/26243266
http://dx.doi.org/10.1186/s12889-015-2097-3
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