Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.4269/ajtmh.21-0217 http://hdl.handle.net/11449/240048 |
Resumo: | Social isolation is extremely important to minimize the effects of a pandemic. Latin American countries have similar socioeconomic characteristics and health system infrastructures. These countries face difficulties in dealing with the COVID-19 pandemic, and some of them have very high death rates. The government stringency index (GSI) of 12 Latin American countries was gathered from the Oxford COVID-19 Government Response Tracker project. The GSI is calculated by considering nine social distancing and isolation measures. Population data from the United Nations Population Fund and number-of-deaths data were collected from the dashboard of the WHO. We performed an analysis of the data collected from March through December 2020 using a mixed linear model. Peru, Brazil, Chile, Bolivia, Colombia, Argentina, and Ecuador had the highest death rates, with an increasing trend over time. Suriname, Venezuela, Uruguay, Paraguay, and Guyana had the lowest death rates, and these rates remained steady. The GSI in most countries followed the same pattern during the months analyzed. In other words, high indices at the beginning of the pandemic and lower indices in the latter months, whereas the number of deaths increased during the entire period. Almost no country kept its GSI high for a long time, especially from October to December. Time and GSI, as well as their interaction, were highly significant. As their interaction increases, the death rate decreases. In conclusion, a greater GSI at the start of the COVID-19 pandemic was associated with a decrease in the number of deaths over time in Latin American countries. |
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Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American CountriesSocial isolation is extremely important to minimize the effects of a pandemic. Latin American countries have similar socioeconomic characteristics and health system infrastructures. These countries face difficulties in dealing with the COVID-19 pandemic, and some of them have very high death rates. The government stringency index (GSI) of 12 Latin American countries was gathered from the Oxford COVID-19 Government Response Tracker project. The GSI is calculated by considering nine social distancing and isolation measures. Population data from the United Nations Population Fund and number-of-deaths data were collected from the dashboard of the WHO. We performed an analysis of the data collected from March through December 2020 using a mixed linear model. Peru, Brazil, Chile, Bolivia, Colombia, Argentina, and Ecuador had the highest death rates, with an increasing trend over time. Suriname, Venezuela, Uruguay, Paraguay, and Guyana had the lowest death rates, and these rates remained steady. The GSI in most countries followed the same pattern during the months analyzed. In other words, high indices at the beginning of the pandemic and lower indices in the latter months, whereas the number of deaths increased during the entire period. Almost no country kept its GSI high for a long time, especially from October to December. Time and GSI, as well as their interaction, were highly significant. As their interaction increases, the death rate decreases. In conclusion, a greater GSI at the start of the COVID-19 pandemic was associated with a decrease in the number of deaths over time in Latin American countries.Life Systems Biology Graduate Program Institute of Biomedical Sciences University of São Paulo (ICB/USP), SPBiosciences Graduate Program Intitute of Biosciences Letters and Exact Sciences São Paulo State University (IBILCE/UNESP), São Jose SP do Rio PretoStructural and Functional Biology Graduate Program Paulista School of Medicine Federal University of Sao Paulo (EPM/UNIFESP), SPDepartment of Physiotherapy University of Fortaleza (UNIFOR), CESchool of Public Health University of São Paulo (FSP/USP), SPDepartment of Medicine University of Fortaleza (UNIFOR), CEDepartment of Statistics and Applied Math Federal University of Ceara (UFC), CEBiosciences Graduate Program Intitute of Biosciences Letters and Exact Sciences São Paulo State University (IBILCE/UNESP), São Jose SP do Rio PretoUniversidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)University of Fortaleza (UNIFOR)Federal University of Ceara (UFC)Silva, Rafael Andre da [UNESP]Ferreira, Luiz Philipe de SouzaLeite, Jean Michel Rocha SampaioTiraboschi, Fernanda AssunçãoValente, Thiago MacielRoda, Vinicius Moraes de PaivaSanchez, Jeniffer Johana Duarte2023-03-01T19:59:09Z2023-03-01T19:59:09Z2022-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1486-1490http://dx.doi.org/10.4269/ajtmh.21-0217American Journal of Tropical Medicine and Hygiene, v. 106, n. 5, p. 1486-1490, 2022.1476-16450002-9637http://hdl.handle.net/11449/24004810.4269/ajtmh.21-02172-s2.0-85129946643Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAmerican Journal of Tropical Medicine and Hygieneinfo:eu-repo/semantics/openAccess2023-03-01T19:59:10Zoai:repositorio.unesp.br:11449/240048Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:50:50.107554Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
title |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
spellingShingle |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries Silva, Rafael Andre da [UNESP] |
title_short |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
title_full |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
title_fullStr |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
title_full_unstemmed |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
title_sort |
Statistical Modeling of Deaths from COVID-19 Influenced by Social Isolation in Latin American Countries |
author |
Silva, Rafael Andre da [UNESP] |
author_facet |
Silva, Rafael Andre da [UNESP] Ferreira, Luiz Philipe de Souza Leite, Jean Michel Rocha Sampaio Tiraboschi, Fernanda Assunção Valente, Thiago Maciel Roda, Vinicius Moraes de Paiva Sanchez, Jeniffer Johana Duarte |
author_role |
author |
author2 |
Ferreira, Luiz Philipe de Souza Leite, Jean Michel Rocha Sampaio Tiraboschi, Fernanda Assunção Valente, Thiago Maciel Roda, Vinicius Moraes de Paiva Sanchez, Jeniffer Johana Duarte |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Estadual Paulista (UNESP) University of Fortaleza (UNIFOR) Federal University of Ceara (UFC) |
dc.contributor.author.fl_str_mv |
Silva, Rafael Andre da [UNESP] Ferreira, Luiz Philipe de Souza Leite, Jean Michel Rocha Sampaio Tiraboschi, Fernanda Assunção Valente, Thiago Maciel Roda, Vinicius Moraes de Paiva Sanchez, Jeniffer Johana Duarte |
description |
Social isolation is extremely important to minimize the effects of a pandemic. Latin American countries have similar socioeconomic characteristics and health system infrastructures. These countries face difficulties in dealing with the COVID-19 pandemic, and some of them have very high death rates. The government stringency index (GSI) of 12 Latin American countries was gathered from the Oxford COVID-19 Government Response Tracker project. The GSI is calculated by considering nine social distancing and isolation measures. Population data from the United Nations Population Fund and number-of-deaths data were collected from the dashboard of the WHO. We performed an analysis of the data collected from March through December 2020 using a mixed linear model. Peru, Brazil, Chile, Bolivia, Colombia, Argentina, and Ecuador had the highest death rates, with an increasing trend over time. Suriname, Venezuela, Uruguay, Paraguay, and Guyana had the lowest death rates, and these rates remained steady. The GSI in most countries followed the same pattern during the months analyzed. In other words, high indices at the beginning of the pandemic and lower indices in the latter months, whereas the number of deaths increased during the entire period. Almost no country kept its GSI high for a long time, especially from October to December. Time and GSI, as well as their interaction, were highly significant. As their interaction increases, the death rate decreases. In conclusion, a greater GSI at the start of the COVID-19 pandemic was associated with a decrease in the number of deaths over time in Latin American countries. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-05-01 2023-03-01T19:59:09Z 2023-03-01T19:59:09Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.4269/ajtmh.21-0217 American Journal of Tropical Medicine and Hygiene, v. 106, n. 5, p. 1486-1490, 2022. 1476-1645 0002-9637 http://hdl.handle.net/11449/240048 10.4269/ajtmh.21-0217 2-s2.0-85129946643 |
url |
http://dx.doi.org/10.4269/ajtmh.21-0217 http://hdl.handle.net/11449/240048 |
identifier_str_mv |
American Journal of Tropical Medicine and Hygiene, v. 106, n. 5, p. 1486-1490, 2022. 1476-1645 0002-9637 10.4269/ajtmh.21-0217 2-s2.0-85129946643 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
American Journal of Tropical Medicine and Hygiene |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1486-1490 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808128990225891328 |