TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2023 |
| Outros Autores: | , , , , , , , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | por |
| Título da fonte: | Hygeia (Uberlândia) |
| Texto Completo: | https://seer.ufu.br/index.php/hygeia/article/view/63335 |
Resumo: | Data geoprocessing and spatial analysis are important tools for the study of phenomena such as the spread of diseases across the territory and over time. The aim of this study is to analyze, using Exploratory Spatial Data Analysis (ESDA), changes in the geographic distribution patterns of Covid-19 in Brazil in two distinct periods of the pandemic: (i) between April and August 2020; and (ii) between November 2020 and March 2021. For this purpose, Moran's I and LISA were applied to data referring to three epidemiological indicators: accumulated cases, new cases and lethality of the disease. The results found and the visualizations proposed present a broad perspective on the variation of Covid-19 cases in Brazilian regions and contribute to a better understanding of the epidemiological dynamics in Brazil in the first year of the Covid-19 pandemic. |
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TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZILANÁLISE TEMPORAL E ESPACIAL DOS CASOS DE COVID-19 NAS REGIÕES GEOGRÁFICAS IMEDIATAS DO BRASILCoronavírusPandemiaIndicadores epidemiológicosI de MoranLISAGeografia da saúdeCoronavirusPandemicEpidemiological indicatorsMoran’ILISAHealth geographyData geoprocessing and spatial analysis are important tools for the study of phenomena such as the spread of diseases across the territory and over time. The aim of this study is to analyze, using Exploratory Spatial Data Analysis (ESDA), changes in the geographic distribution patterns of Covid-19 in Brazil in two distinct periods of the pandemic: (i) between April and August 2020; and (ii) between November 2020 and March 2021. For this purpose, Moran's I and LISA were applied to data referring to three epidemiological indicators: accumulated cases, new cases and lethality of the disease. The results found and the visualizations proposed present a broad perspective on the variation of Covid-19 cases in Brazilian regions and contribute to a better understanding of the epidemiological dynamics in Brazil in the first year of the Covid-19 pandemic.O geoprocessamento de dados e as análises espaciais são ferramentas importantes para o estudo de fenômenos como a disseminação de doenças pelo território e ao longo do tempo. O objetivo deste estudo é investigar, utilizando a Análise Exploratória de Dados Espaciais (AEDE), as alterações nos padrões de distribuição geográfica da Covid-19 no Brasil em dois períodos distintos da pandemia: (i) entre abril e agosto de 2020; e (ii) entre novembro de 2020 e março de 2021. Para tanto, as estatísticas I de Moran e LISA foram aplicadas aos dados referentes a três indicadores epidemiológicos: casos acumulados, novos casos e letalidade da doença. Os resultados encontrados e as visualizações propostas apresentam uma perspectiva ampla sobre a variação nos casos de Covid-19 nas regiões brasileiras e colaboram para um melhor entendimento sobre as dinâmicas epidemiológicas no Brasil no primeiro ano da pandemia de Covid-19.Universidade Federal de Uberlândia2023-02-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/hygeia/article/view/6333510.14393/Hygeia1963335Hygeia - Revista Brasileira de Geografia Médica e da Saúde; v. 19 (2023); e19031980-1726reponame:Hygeia (Uberlândia)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUporhttps://seer.ufu.br/index.php/hygeia/article/view/63335/35569Copyright (c) 2022 Pedro Loures Alzamora, Evandro Landulfo Teixeira Paradela Cunha Cunha, Daniel Victor Ferreira Victor Ferreira , Tereza Bernardes Bernardes, Janaina Teodoro Guiginski Guiginski, Julia Fonseca de Sena, Isadora Cristina de Matos Rodrigues, Daniel Victor Ferreira Victor Ferreira , Marcelo Ganem Ganem, Marcelo Sartori Locatelli Sartori Locatelli, Thiago Henrique Moreira Santos Henrique Moreira Santos, Evandro Landulfo Teixeira Paradela Cunha Cunha, Ramon Adrian Salinas Franco, Tereza Bernardes Bernardes, Janaina Teodoro Guiginski Guiginski, Ana Paula Couto da Silva Silva, Wagner Meira Junior Juniorinfo:eu-repo/semantics/openAccessAlzamora, Pedro LouresFerreira , Daniel VictorRodrigues, Isadora Cristina de MatosSena, Julia Fonseca deGanem, MarceloLocatelli, Marcelo SartoriSantos, Thiago Henrique MoreiraCunha, Evandro Landulfo Teixeira ParadelaGuiginski, Janaina TeodoroFranco, Ramon Adrian SalinasBernardes, TerezaSilva, Ana Paula Couto daMeira Junior, Wagner2023-03-20T17:31:47Zoai:ojs.www.seer.ufu.br:article/63335Revistahttps://seer.ufu.br/index.php/hygeiaPUBhttps://seer.ufu.br/index.php/hygeia/oaisamuel@ufu.br||flavia.santos@ufu.br1980-17261980-1726opendoar:2023-03-20T17:31:47Hygeia (Uberlândia) - Universidade Federal de Uberlândia (UFU)false |
| dc.title.none.fl_str_mv |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL ANÁLISE TEMPORAL E ESPACIAL DOS CASOS DE COVID-19 NAS REGIÕES GEOGRÁFICAS IMEDIATAS DO BRASIL |
| title |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| spellingShingle |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL Alzamora, Pedro Loures Coronavírus Pandemia Indicadores epidemiológicos I de Moran LISA Geografia da saúde Coronavirus Pandemic Epidemiological indicators Moran’I LISA Health geography |
| title_short |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| title_full |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| title_fullStr |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| title_full_unstemmed |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| title_sort |
TEMPORAL AND SPATIAL ANALYSIS OF COVID-19 CASES IN IMMEDIATE GEOGRAPHIC REGIONS OF BRAZIL |
| author |
Alzamora, Pedro Loures |
| author_facet |
Alzamora, Pedro Loures Ferreira , Daniel Victor Rodrigues, Isadora Cristina de Matos Sena, Julia Fonseca de Ganem, Marcelo Locatelli, Marcelo Sartori Santos, Thiago Henrique Moreira Cunha, Evandro Landulfo Teixeira Paradela Guiginski, Janaina Teodoro Franco, Ramon Adrian Salinas Bernardes, Tereza Silva, Ana Paula Couto da Meira Junior, Wagner |
| author_role |
author |
| author2 |
Ferreira , Daniel Victor Rodrigues, Isadora Cristina de Matos Sena, Julia Fonseca de Ganem, Marcelo Locatelli, Marcelo Sartori Santos, Thiago Henrique Moreira Cunha, Evandro Landulfo Teixeira Paradela Guiginski, Janaina Teodoro Franco, Ramon Adrian Salinas Bernardes, Tereza Silva, Ana Paula Couto da Meira Junior, Wagner |
| author2_role |
author author author author author author author author author author author author |
| dc.contributor.author.fl_str_mv |
Alzamora, Pedro Loures Ferreira , Daniel Victor Rodrigues, Isadora Cristina de Matos Sena, Julia Fonseca de Ganem, Marcelo Locatelli, Marcelo Sartori Santos, Thiago Henrique Moreira Cunha, Evandro Landulfo Teixeira Paradela Guiginski, Janaina Teodoro Franco, Ramon Adrian Salinas Bernardes, Tereza Silva, Ana Paula Couto da Meira Junior, Wagner |
| dc.subject.por.fl_str_mv |
Coronavírus Pandemia Indicadores epidemiológicos I de Moran LISA Geografia da saúde Coronavirus Pandemic Epidemiological indicators Moran’I LISA Health geography |
| topic |
Coronavírus Pandemia Indicadores epidemiológicos I de Moran LISA Geografia da saúde Coronavirus Pandemic Epidemiological indicators Moran’I LISA Health geography |
| description |
Data geoprocessing and spatial analysis are important tools for the study of phenomena such as the spread of diseases across the territory and over time. The aim of this study is to analyze, using Exploratory Spatial Data Analysis (ESDA), changes in the geographic distribution patterns of Covid-19 in Brazil in two distinct periods of the pandemic: (i) between April and August 2020; and (ii) between November 2020 and March 2021. For this purpose, Moran's I and LISA were applied to data referring to three epidemiological indicators: accumulated cases, new cases and lethality of the disease. The results found and the visualizations proposed present a broad perspective on the variation of Covid-19 cases in Brazilian regions and contribute to a better understanding of the epidemiological dynamics in Brazil in the first year of the Covid-19 pandemic. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-02-14 |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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https://seer.ufu.br/index.php/hygeia/article/view/63335 10.14393/Hygeia1963335 |
| url |
https://seer.ufu.br/index.php/hygeia/article/view/63335 |
| identifier_str_mv |
10.14393/Hygeia1963335 |
| dc.language.iso.fl_str_mv |
por |
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por |
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https://seer.ufu.br/index.php/hygeia/article/view/63335/35569 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
| dc.publisher.none.fl_str_mv |
Universidade Federal de Uberlândia |
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Universidade Federal de Uberlândia |
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Hygeia - Revista Brasileira de Geografia Médica e da Saúde; v. 19 (2023); e1903 1980-1726 reponame:Hygeia (Uberlândia) instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
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Universidade Federal de Uberlândia (UFU) |
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UFU |
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UFU |
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Hygeia (Uberlândia) |
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Hygeia (Uberlândia) |
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Hygeia (Uberlândia) - Universidade Federal de Uberlândia (UFU) |
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samuel@ufu.br||flavia.santos@ufu.br |
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