High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Saúde Pública |
Texto Completo: | https://www.revistas.usp.br/rsp/article/view/213399 |
Resumo: | OBJECTIVE: To analyze the spatial distribution and identify high-risk spatial clusters of Zika, dengue, and chikungunya (ZDC), in the city of Rio de Janeiro, Brazil, and their socioeconomic status. METHODS: An ecological study based on data from a seroprevalence survey. Using a rapid diagnostic test to detect the arboviruses, 2,114 individuals were tested in 2018. The spatial distribution was analyzed using kernel estimation. To detect high-risk spatial clusters of arboviruses, we used multivariate scan statistics. The Social Development Index (SDI) was considered in the analysis of socioeconomic status. RESULTS: Among the 2,114 individuals, 1,714 (81.1%) were positive for at least one arbovirus investigated. The kernel estimation showed positive individuals for at least one arbovirus in all regions of the city, with hot spots in the North, coincident with regions with very low or low SDI. The scan statistic detected three significant (p<0.05) high-risk spatial clusters for Zika, dengue, and chikungunya viruses. These clusters correspond to 35.7% (n=613) of all positive individuals of the sample. The most likely cluster was in the North (cluster 1) and overlapped regions with very low and low SDI. Clusters 2 and 3 were in the West and overlapping regions with low and very low SDI, respectively. The highest values of relative risks were in cluster 1 for CHIKV (1.97), in cluster 2 for ZIKV (1.58), and in cluster 3 for CHIKV (1.44). Regarding outcomes in the clusters, the Flavivirus had the highest frequency in clusters 1, 2, and 3 (42.83%, 54.46%, and 52.08%, respectively). CONCLUSION: We found an over-risk for arboviruses in areas with the worst socioeconomic conditions in Rio de Janeiro. Moreover, the highest concentration of people negative for arboviruses occurred in areas considered to have better living conditions. |
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High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, BrazilZikaDengueChikungunyaEpidemiologySpatial AnalysisCluster DetectionEcological StudiesOBJECTIVE: To analyze the spatial distribution and identify high-risk spatial clusters of Zika, dengue, and chikungunya (ZDC), in the city of Rio de Janeiro, Brazil, and their socioeconomic status. METHODS: An ecological study based on data from a seroprevalence survey. Using a rapid diagnostic test to detect the arboviruses, 2,114 individuals were tested in 2018. The spatial distribution was analyzed using kernel estimation. To detect high-risk spatial clusters of arboviruses, we used multivariate scan statistics. The Social Development Index (SDI) was considered in the analysis of socioeconomic status. RESULTS: Among the 2,114 individuals, 1,714 (81.1%) were positive for at least one arbovirus investigated. The kernel estimation showed positive individuals for at least one arbovirus in all regions of the city, with hot spots in the North, coincident with regions with very low or low SDI. The scan statistic detected three significant (p<0.05) high-risk spatial clusters for Zika, dengue, and chikungunya viruses. These clusters correspond to 35.7% (n=613) of all positive individuals of the sample. The most likely cluster was in the North (cluster 1) and overlapped regions with very low and low SDI. Clusters 2 and 3 were in the West and overlapping regions with low and very low SDI, respectively. The highest values of relative risks were in cluster 1 for CHIKV (1.97), in cluster 2 for ZIKV (1.58), and in cluster 3 for CHIKV (1.44). Regarding outcomes in the clusters, the Flavivirus had the highest frequency in clusters 1, 2, and 3 (42.83%, 54.46%, and 52.08%, respectively). CONCLUSION: We found an over-risk for arboviruses in areas with the worst socioeconomic conditions in Rio de Janeiro. Moreover, the highest concentration of people negative for arboviruses occurred in areas considered to have better living conditions.Universidade de São Paulo. Faculdade de Saúde Pública2023-05-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/xmlhttps://www.revistas.usp.br/rsp/article/view/21339910.11606/s1518-8787.2023057004932Revista de Saúde Pública; Vol. 57 No. 1 (2023); 32Revista de Saúde Pública; Vol. 57 Núm. 1 (2023); 32Revista de Saúde Pública; v. 57 n. 1 (2023); 321518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/rsp/article/view/213399/195336https://www.revistas.usp.br/rsp/article/view/213399/195335Copyright (c) 2023 Reinaldo Souza-Santos, Andrea Sobral, Andre Reynaldo Santos Périsséhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSouza-Santos, ReinaldoSobral, AndreaPérissé, Andre Reynaldo Santos2023-06-20T20:36:44Zoai:revistas.usp.br:article/213399Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2023-06-20T20:36:44Revista de Saúde Pública - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
title |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
spellingShingle |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil Souza-Santos, Reinaldo Zika Dengue Chikungunya Epidemiology Spatial Analysis Cluster Detection Ecological Studies |
title_short |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
title_full |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
title_fullStr |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
title_full_unstemmed |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
title_sort |
High-risk spatial clusters for Zika, dengue, and chikungunya in Rio de Janeiro, Brazil |
author |
Souza-Santos, Reinaldo |
author_facet |
Souza-Santos, Reinaldo Sobral, Andrea Périssé, Andre Reynaldo Santos |
author_role |
author |
author2 |
Sobral, Andrea Périssé, Andre Reynaldo Santos |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Souza-Santos, Reinaldo Sobral, Andrea Périssé, Andre Reynaldo Santos |
dc.subject.por.fl_str_mv |
Zika Dengue Chikungunya Epidemiology Spatial Analysis Cluster Detection Ecological Studies |
topic |
Zika Dengue Chikungunya Epidemiology Spatial Analysis Cluster Detection Ecological Studies |
description |
OBJECTIVE: To analyze the spatial distribution and identify high-risk spatial clusters of Zika, dengue, and chikungunya (ZDC), in the city of Rio de Janeiro, Brazil, and their socioeconomic status. METHODS: An ecological study based on data from a seroprevalence survey. Using a rapid diagnostic test to detect the arboviruses, 2,114 individuals were tested in 2018. The spatial distribution was analyzed using kernel estimation. To detect high-risk spatial clusters of arboviruses, we used multivariate scan statistics. The Social Development Index (SDI) was considered in the analysis of socioeconomic status. RESULTS: Among the 2,114 individuals, 1,714 (81.1%) were positive for at least one arbovirus investigated. The kernel estimation showed positive individuals for at least one arbovirus in all regions of the city, with hot spots in the North, coincident with regions with very low or low SDI. The scan statistic detected three significant (p<0.05) high-risk spatial clusters for Zika, dengue, and chikungunya viruses. These clusters correspond to 35.7% (n=613) of all positive individuals of the sample. The most likely cluster was in the North (cluster 1) and overlapped regions with very low and low SDI. Clusters 2 and 3 were in the West and overlapping regions with low and very low SDI, respectively. The highest values of relative risks were in cluster 1 for CHIKV (1.97), in cluster 2 for ZIKV (1.58), and in cluster 3 for CHIKV (1.44). Regarding outcomes in the clusters, the Flavivirus had the highest frequency in clusters 1, 2, and 3 (42.83%, 54.46%, and 52.08%, respectively). CONCLUSION: We found an over-risk for arboviruses in areas with the worst socioeconomic conditions in Rio de Janeiro. Moreover, the highest concentration of people negative for arboviruses occurred in areas considered to have better living conditions. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-05-30 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/213399 10.11606/s1518-8787.2023057004932 |
url |
https://www.revistas.usp.br/rsp/article/view/213399 |
identifier_str_mv |
10.11606/s1518-8787.2023057004932 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/213399/195336 https://www.revistas.usp.br/rsp/article/view/213399/195335 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Reinaldo Souza-Santos, Andrea Sobral, Andre Reynaldo Santos Périssé https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Reinaldo Souza-Santos, Andrea Sobral, Andre Reynaldo Santos Périssé https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/xml |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
dc.source.none.fl_str_mv |
Revista de Saúde Pública; Vol. 57 No. 1 (2023); 32 Revista de Saúde Pública; Vol. 57 Núm. 1 (2023); 32 Revista de Saúde Pública; v. 57 n. 1 (2023); 32 1518-8787 0034-8910 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_ |
1800221803926257664 |