Geoclimatic, demographic and socioeconomic characteristics related to dengue outbreaks in Southeastern Brazil: an annual spatial and spatiotemporal risk model over a 12-year period

Detalhes bibliográficos
Autor(a) principal: Vernal, Sebastian
Data de Publicação: 2021
Outros Autores: Nahas, Andressa K., Chiaravalloti Neto, Francisco, Prete Junior, Carlos A., Cortez, André L., Sabino, Ester Cerdeira, Luna, Expedito José de Albuquerque
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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spelling 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
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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)
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