Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista do Instituto de Medicina Tropical de São Paulo |
Texto Completo: | https://www.revistas.usp.br/rimtsp/article/view/191024 |
Resumo: | Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil. |
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Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year periodDengueArbovirusInfectious diseases outbreakEpidemiologic studySpatiotemporal analysisDengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil.Universidade de São Paulo. Instituto de Medicina Tropical de São Paulo2021-09-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/rimtsp/article/view/19102410.1590/S1678-9946202163070 Revista do Instituto de Medicina Tropical de São Paulo; Vol. 63 (2021); e70Revista do Instituto de Medicina Tropical de São Paulo; Vol. 63 (2021); e70Revista do Instituto de Medicina Tropical de São Paulo; v. 63 (2021); e701678-99460036-4665reponame:Revista do Instituto de Medicina Tropical de São Pauloinstname:Instituto de Medicina Tropical (IMT)instacron:IMTenghttps://www.revistas.usp.br/rimtsp/article/view/191024/176107Copyright (c) 2021 Sebastian Vernal, Andressa K. Nahas, Francisco Chiaravalloti Neto, Carlos A. Prete Junior, André L. Cortez, Ester Cerdeira Sabino, Expedito José de Albuquerque Lunahttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessVernal, Sebastian Nahas, Andressa K. Chiaravalloti Neto, Francisco Prete Junior, Carlos A. Cortez, André L. Sabino, Ester Cerdeira Luna, Expedito José de Albuquerque 2022-05-16T13:44:35Zoai:revistas.usp.br:article/191024Revistahttp://www.revistas.usp.br/rimtsp/indexPUBhttps://www.revistas.usp.br/rimtsp/oai||revimtsp@usp.br1678-99460036-4665opendoar:2022-12-13T16:52:59.859103Revista do Instituto de Medicina Tropical de São Paulo - Instituto de Medicina Tropical (IMT)true |
dc.title.none.fl_str_mv |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
title |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
spellingShingle |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period Vernal, Sebastian Dengue Arbovirus Infectious diseases outbreak Epidemiologic study Spatiotemporal analysis |
title_short |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
title_full |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
title_fullStr |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
title_full_unstemmed |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
title_sort |
Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period |
author |
Vernal, Sebastian |
author_facet |
Vernal, Sebastian Nahas, Andressa K. Chiaravalloti Neto, Francisco Prete Junior, Carlos A. Cortez, André L. Sabino, Ester Cerdeira Luna, Expedito José de Albuquerque |
author_role |
author |
author2 |
Nahas, Andressa K. Chiaravalloti Neto, Francisco Prete Junior, Carlos A. Cortez, André L. Sabino, Ester Cerdeira Luna, Expedito José de Albuquerque |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Vernal, Sebastian Nahas, Andressa K. Chiaravalloti Neto, Francisco Prete Junior, Carlos A. Cortez, André L. Sabino, Ester Cerdeira Luna, Expedito José de Albuquerque |
dc.subject.por.fl_str_mv |
Dengue Arbovirus Infectious diseases outbreak Epidemiologic study Spatiotemporal analysis |
topic |
Dengue Arbovirus Infectious diseases outbreak Epidemiologic study Spatiotemporal analysis |
description |
Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-29 |
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/rimtsp/article/view/191024 10.1590/S1678-9946202163070 |
url |
https://www.revistas.usp.br/rimtsp/article/view/191024 |
identifier_str_mv |
10.1590/S1678-9946202163070 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/rimtsp/article/view/191024/176107 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Instituto de Medicina Tropical de São Paulo |
publisher.none.fl_str_mv |
Universidade de São Paulo. Instituto de Medicina Tropical de São Paulo |
dc.source.none.fl_str_mv |
Revista do Instituto de Medicina Tropical de São Paulo; Vol. 63 (2021); e70 Revista do Instituto de Medicina Tropical de São Paulo; Vol. 63 (2021); e70 Revista do Instituto de Medicina Tropical de São Paulo; v. 63 (2021); e70 1678-9946 0036-4665 reponame:Revista do Instituto de Medicina Tropical de São Paulo instname:Instituto de Medicina Tropical (IMT) instacron:IMT |
instname_str |
Instituto de Medicina Tropical (IMT) |
instacron_str |
IMT |
institution |
IMT |
reponame_str |
Revista do Instituto de Medicina Tropical de São Paulo |
collection |
Revista do Instituto de Medicina Tropical de São Paulo |
repository.name.fl_str_mv |
Revista do Instituto de Medicina Tropical de São Paulo - Instituto de Medicina Tropical (IMT) |
repository.mail.fl_str_mv |
||revimtsp@usp.br |
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1798951653254103040 |