Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | preprint |
Idioma: | por |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/2212 |
Resumo: | Objective: To describe the space-time evolution of cases and deaths due to COVID-19 in the Rio de Janeiro municipality during the first year of the pandemic. Methods: We carried out an ecological study whose units of analysis were the neighborhoods of the municipality of Rio de Janeiro. We calculated Incidence and mortality rates, excess risk, global Moran index (Moran's I), Local indicator of spatial association (LISA), standardized incidence ratio (SIR) and standardized mortality ratio (SMR) for neighborhoods in the municipality of Rio de Janeiro. Results: Over the first year, City of Rio de Janeiro registries included 204,888 cases and 19,017 deaths due to COVID-19. During the first three months of the pandemic, the municipality show higher incidence rates than the State of Rio de Janeiro and Brazil and higher mortality rates than the State of Rio de Janeiro and Brazil from May 2020 to February 2021. Bonsucesso was the neighborhood with the highest incidence and mortality rates, and throughout the communities and months, there is no synchrony between the worst moments of the COVID-19 pandemic. Conclusions: We emphasize the need to implement more rigid control and prevention measures, increase case detection, and accelerate the COVID-19 immunization campaign. |
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Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipalityAnálise espaço-temporal do primeiro ano da pandemia de COVID-19 no município do Rio de JaneiroCOVID-19SARS CoV-2Análise EspacialEpidemiologiaBrasilCOVID-19SARS CoV-2Spatial AnalysisEpidemiologyBrazilObjective: To describe the space-time evolution of cases and deaths due to COVID-19 in the Rio de Janeiro municipality during the first year of the pandemic. Methods: We carried out an ecological study whose units of analysis were the neighborhoods of the municipality of Rio de Janeiro. We calculated Incidence and mortality rates, excess risk, global Moran index (Moran's I), Local indicator of spatial association (LISA), standardized incidence ratio (SIR) and standardized mortality ratio (SMR) for neighborhoods in the municipality of Rio de Janeiro. Results: Over the first year, City of Rio de Janeiro registries included 204,888 cases and 19,017 deaths due to COVID-19. During the first three months of the pandemic, the municipality show higher incidence rates than the State of Rio de Janeiro and Brazil and higher mortality rates than the State of Rio de Janeiro and Brazil from May 2020 to February 2021. Bonsucesso was the neighborhood with the highest incidence and mortality rates, and throughout the communities and months, there is no synchrony between the worst moments of the COVID-19 pandemic. Conclusions: We emphasize the need to implement more rigid control and prevention measures, increase case detection, and accelerate the COVID-19 immunization campaign.Objetivo: descrever a evolução espaço-temporal de detecção de casos e mortalidade por COVID-19 no município do Rio de Janeiro durante o primeiro ano da pandemia. Métodos: foi realizado um estudo ecológico cujas unidades de análise foram os bairros do município do Rio de Janeiro. Foram calculadas as taxas de incidência e mortalidade, excesso de risco, índice de Moran global (I de Moran), indicador local de associação espacial (LISA), razão de incidência padronizada (SIR) e razão de mortalidade padronizada (SMR) para bairros do município do Rio de Janeiro. Resultados: foram notificados 204.888 casos e 19.017 óbitos por COVID-19, o município apresentou durante os 3 primeiros meses de pandemia taxas de incidência superiores ao Estado do Rio de Janeiro e ao Brasil e taxas de mortalidade superiores ao Estado do Rio de Janeiro e Brasil a partir de maio de 2020 até fevereiro de 2021. Bonsucesso foi o bairro com maiores taxas de incidência e mortalidade, e aos longo dos bairros e dos meses não há sincronia entre os piores momentos da pandemia de COVID-19 Conclusões: ressaltamos a necessidade de implantação de medidas mais rígidas para controle e prevenção, aumento na detecção de casos e a aceleração da campanha de imunização da COVID-19.SciELO PreprintsSciELO PreprintsSciELO Preprints2021-05-05info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/221210.1590/SciELOPreprints.2212porhttps://preprints.scielo.org/index.php/scielo/article/view/2212/3678Copyright (c) 2021 Cleber Vinicuis Brito dos Santos, João Roberto Cavalcante, Paula Cristina Pungartnik, Raphael Mendonça Guimarãeshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSantos, Cleber Vinicuis Brito dosCavalcante, João RobertoPungartnik, Paula CristinaGuimarães, Raphael Mendonçareponame:SciELO Preprintsinstname:SciELOinstacron:SCI2021-05-05T16:21:40Zoai:ops.preprints.scielo.org:preprint/2212Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2021-05-05T16:21:40SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality Análise espaço-temporal do primeiro ano da pandemia de COVID-19 no município do Rio de Janeiro |
title |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
spellingShingle |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality Santos, Cleber Vinicuis Brito dos COVID-19 SARS CoV-2 Análise Espacial Epidemiologia Brasil COVID-19 SARS CoV-2 Spatial Analysis Epidemiology Brazil |
title_short |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
title_full |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
title_fullStr |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
title_full_unstemmed |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
title_sort |
Space-time analysis of the first year of COVID-19 pandemic in Rio de Janeiro municipality |
author |
Santos, Cleber Vinicuis Brito dos |
author_facet |
Santos, Cleber Vinicuis Brito dos Cavalcante, João Roberto Pungartnik, Paula Cristina Guimarães, Raphael Mendonça |
author_role |
author |
author2 |
Cavalcante, João Roberto Pungartnik, Paula Cristina Guimarães, Raphael Mendonça |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Santos, Cleber Vinicuis Brito dos Cavalcante, João Roberto Pungartnik, Paula Cristina Guimarães, Raphael Mendonça |
dc.subject.por.fl_str_mv |
COVID-19 SARS CoV-2 Análise Espacial Epidemiologia Brasil COVID-19 SARS CoV-2 Spatial Analysis Epidemiology Brazil |
topic |
COVID-19 SARS CoV-2 Análise Espacial Epidemiologia Brasil COVID-19 SARS CoV-2 Spatial Analysis Epidemiology Brazil |
description |
Objective: To describe the space-time evolution of cases and deaths due to COVID-19 in the Rio de Janeiro municipality during the first year of the pandemic. Methods: We carried out an ecological study whose units of analysis were the neighborhoods of the municipality of Rio de Janeiro. We calculated Incidence and mortality rates, excess risk, global Moran index (Moran's I), Local indicator of spatial association (LISA), standardized incidence ratio (SIR) and standardized mortality ratio (SMR) for neighborhoods in the municipality of Rio de Janeiro. Results: Over the first year, City of Rio de Janeiro registries included 204,888 cases and 19,017 deaths due to COVID-19. During the first three months of the pandemic, the municipality show higher incidence rates than the State of Rio de Janeiro and Brazil and higher mortality rates than the State of Rio de Janeiro and Brazil from May 2020 to February 2021. Bonsucesso was the neighborhood with the highest incidence and mortality rates, and throughout the communities and months, there is no synchrony between the worst moments of the COVID-19 pandemic. Conclusions: We emphasize the need to implement more rigid control and prevention measures, increase case detection, and accelerate the COVID-19 immunization campaign. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-05-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/2212 10.1590/SciELOPreprints.2212 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/2212 |
identifier_str_mv |
10.1590/SciELOPreprints.2212 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/2212/3678 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO |
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SciELO Preprints |
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SciELO Preprints - SciELO |
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