Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America

Autores
Mantilla Caicedo, Gilma C.; Rusticucci, Matilde Monica; Suli, Solange; Dankiewicz, Verónica; Salvador, Ayala; Caiman Peñarete, Alexandra; Diaz, Martin; Fontán, Silvia; Chesini, Francisco; Jiménez Buitrago, Diana; Barreto Pedraza, Luis; Barrera, Facundo Matías
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This study aimed to analyse how socio-environmental conditions affected the early evolution of COVID-19 in 14 urban sites in South America based on a spatio-temporal multidisciplinary approach. The daily incidence rate of new COVID-19 cases with symptoms as the dependent variable and meteorological-climatic data (mean, maximum, and minimum temperature, precipitation, and relative humidity) as the independent variables were analysed. The study period was from March to November of 2020. We inquired associations of these variables with COVID-19 data using Spearman´s non-parametric correlation test, and a principal component analysis considering socio economic and demographic variables, new cases, and rates of COVID-19 new cases. Finally, an analysis using non-metric multidimensional scale ordering by the Bray-Curtis similarity matrix of meteorological data, socio economic ando- demographic variables, and COVID-19 was performed. Our findings revealed that the average, maximum, and minimum temperatures and relative humidity were significantly associated with rates of COVID-19 new cases in most of the sites, while precipitation was significantly associated only in four sites. Additionally, demographic variables such as the number of inhabitants, the percentage of the population aged 60 years and above, the masculinity index, and the GINI index showed a significant correlation with COVID-19 cases. Due to the rapid evolution of the COVID-19 pandemic, these findings provide strong evidence that biomedical, social, and physical sciences should join forces in truly multidisciplinary research that is critically needed in the current state of our region.
Fil: Mantilla Caicedo, Gilma C.. Columbia University; Estados Unidos
Fil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Suli, Solange. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Dankiewicz, Verónica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Salvador, Ayala. Universidad de Chile; Chile
Fil: Caiman Peñarete, Alexandra. Red Hospitalaria Bogotá Distrito Capital; Colombia
Fil: Diaz, Martin. Universidad Nacional de La Matanza; Argentina
Fil: Fontán, Silvia. Universidad Nacional de La Matanza; Argentina
Fil: Chesini, Francisco. Ministerio de Salud de la Nación; Argentina
Fil: Jiménez Buitrago, Diana. Ministerio de Salud y Protección Social; Colombia
Fil: Barreto Pedraza, Luis. Instituto de Hidrología, Meteorología y Estudios Ambien; Colombia
Fil: Barrera, Facundo Matías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
Materia
CLIMATE VARIABILITY
SARS-CoV-2
PANDEMIC
PARAMETRIC AND NON-PARAMETRIC ANALYSIS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/231503
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/231503
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South AmericaMantilla Caicedo, Gilma C.Rusticucci, Matilde MonicaSuli, SolangeDankiewicz, VerónicaSalvador, AyalaCaiman Peñarete, AlexandraDiaz, MartinFontán, SilviaChesini, FranciscoJiménez Buitrago, DianaBarreto Pedraza, LuisBarrera, Facundo MatíasCLIMATE VARIABILITYSARS-CoV-2PANDEMICPARAMETRIC AND NON-PARAMETRIC ANALYSIShttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3This study aimed to analyse how socio-environmental conditions affected the early evolution of COVID-19 in 14 urban sites in South America based on a spatio-temporal multidisciplinary approach. The daily incidence rate of new COVID-19 cases with symptoms as the dependent variable and meteorological-climatic data (mean, maximum, and minimum temperature, precipitation, and relative humidity) as the independent variables were analysed. The study period was from March to November of 2020. We inquired associations of these variables with COVID-19 data using Spearman´s non-parametric correlation test, and a principal component analysis considering socio economic and demographic variables, new cases, and rates of COVID-19 new cases. Finally, an analysis using non-metric multidimensional scale ordering by the Bray-Curtis similarity matrix of meteorological data, socio economic ando- demographic variables, and COVID-19 was performed. Our findings revealed that the average, maximum, and minimum temperatures and relative humidity were significantly associated with rates of COVID-19 new cases in most of the sites, while precipitation was significantly associated only in four sites. Additionally, demographic variables such as the number of inhabitants, the percentage of the population aged 60 years and above, the masculinity index, and the GINI index showed a significant correlation with COVID-19 cases. Due to the rapid evolution of the COVID-19 pandemic, these findings provide strong evidence that biomedical, social, and physical sciences should join forces in truly multidisciplinary research that is critically needed in the current state of our region.Fil: Mantilla Caicedo, Gilma C.. Columbia University; Estados UnidosFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Suli, Solange. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Dankiewicz, Verónica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Salvador, Ayala. Universidad de Chile; ChileFil: Caiman Peñarete, Alexandra. Red Hospitalaria Bogotá Distrito Capital; ColombiaFil: Diaz, Martin. Universidad Nacional de La Matanza; ArgentinaFil: Fontán, Silvia. Universidad Nacional de La Matanza; ArgentinaFil: Chesini, Francisco. Ministerio de Salud de la Nación; ArgentinaFil: Jiménez Buitrago, Diana. Ministerio de Salud y Protección Social; ColombiaFil: Barreto Pedraza, Luis. Instituto de Hidrología, Meteorología y Estudios Ambien; ColombiaFil: Barrera, Facundo Matías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaElsevier2023-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/231503Mantilla Caicedo, Gilma C.; Rusticucci, Matilde Monica; Suli, Solange; Dankiewicz, Verónica; Salvador, Ayala; et al.; Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America; Elsevier; Heliyon; 9; 5; 5-2023; 1-152405-8440CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.heliyon.2023.e16056info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2405844023032632info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:31:08Zoai:ri.conicet.gov.ar:11336/231503instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:31:09.296CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
title Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
spellingShingle Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
Mantilla Caicedo, Gilma C.
CLIMATE VARIABILITY
SARS-CoV-2
PANDEMIC
PARAMETRIC AND NON-PARAMETRIC ANALYSIS
title_short Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
title_full Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
title_fullStr Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
title_full_unstemmed Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
title_sort Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America
dc.creator.none.fl_str_mv Mantilla Caicedo, Gilma C.
Rusticucci, Matilde Monica
Suli, Solange
Dankiewicz, Verónica
Salvador, Ayala
Caiman Peñarete, Alexandra
Diaz, Martin
Fontán, Silvia
Chesini, Francisco
Jiménez Buitrago, Diana
Barreto Pedraza, Luis
Barrera, Facundo Matías
author Mantilla Caicedo, Gilma C.
author_facet Mantilla Caicedo, Gilma C.
Rusticucci, Matilde Monica
Suli, Solange
Dankiewicz, Verónica
Salvador, Ayala
Caiman Peñarete, Alexandra
Diaz, Martin
Fontán, Silvia
Chesini, Francisco
Jiménez Buitrago, Diana
Barreto Pedraza, Luis
Barrera, Facundo Matías
author_role author
author2 Rusticucci, Matilde Monica
Suli, Solange
Dankiewicz, Verónica
Salvador, Ayala
Caiman Peñarete, Alexandra
Diaz, Martin
Fontán, Silvia
Chesini, Francisco
Jiménez Buitrago, Diana
Barreto Pedraza, Luis
Barrera, Facundo Matías
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv CLIMATE VARIABILITY
SARS-CoV-2
PANDEMIC
PARAMETRIC AND NON-PARAMETRIC ANALYSIS
topic CLIMATE VARIABILITY
SARS-CoV-2
PANDEMIC
PARAMETRIC AND NON-PARAMETRIC ANALYSIS
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv This study aimed to analyse how socio-environmental conditions affected the early evolution of COVID-19 in 14 urban sites in South America based on a spatio-temporal multidisciplinary approach. The daily incidence rate of new COVID-19 cases with symptoms as the dependent variable and meteorological-climatic data (mean, maximum, and minimum temperature, precipitation, and relative humidity) as the independent variables were analysed. The study period was from March to November of 2020. We inquired associations of these variables with COVID-19 data using Spearman´s non-parametric correlation test, and a principal component analysis considering socio economic and demographic variables, new cases, and rates of COVID-19 new cases. Finally, an analysis using non-metric multidimensional scale ordering by the Bray-Curtis similarity matrix of meteorological data, socio economic ando- demographic variables, and COVID-19 was performed. Our findings revealed that the average, maximum, and minimum temperatures and relative humidity were significantly associated with rates of COVID-19 new cases in most of the sites, while precipitation was significantly associated only in four sites. Additionally, demographic variables such as the number of inhabitants, the percentage of the population aged 60 years and above, the masculinity index, and the GINI index showed a significant correlation with COVID-19 cases. Due to the rapid evolution of the COVID-19 pandemic, these findings provide strong evidence that biomedical, social, and physical sciences should join forces in truly multidisciplinary research that is critically needed in the current state of our region.
Fil: Mantilla Caicedo, Gilma C.. Columbia University; Estados Unidos
Fil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Suli, Solange. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Dankiewicz, Verónica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Salvador, Ayala. Universidad de Chile; Chile
Fil: Caiman Peñarete, Alexandra. Red Hospitalaria Bogotá Distrito Capital; Colombia
Fil: Diaz, Martin. Universidad Nacional de La Matanza; Argentina
Fil: Fontán, Silvia. Universidad Nacional de La Matanza; Argentina
Fil: Chesini, Francisco. Ministerio de Salud de la Nación; Argentina
Fil: Jiménez Buitrago, Diana. Ministerio de Salud y Protección Social; Colombia
Fil: Barreto Pedraza, Luis. Instituto de Hidrología, Meteorología y Estudios Ambien; Colombia
Fil: Barrera, Facundo Matías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
description This study aimed to analyse how socio-environmental conditions affected the early evolution of COVID-19 in 14 urban sites in South America based on a spatio-temporal multidisciplinary approach. The daily incidence rate of new COVID-19 cases with symptoms as the dependent variable and meteorological-climatic data (mean, maximum, and minimum temperature, precipitation, and relative humidity) as the independent variables were analysed. The study period was from March to November of 2020. We inquired associations of these variables with COVID-19 data using Spearman´s non-parametric correlation test, and a principal component analysis considering socio economic and demographic variables, new cases, and rates of COVID-19 new cases. Finally, an analysis using non-metric multidimensional scale ordering by the Bray-Curtis similarity matrix of meteorological data, socio economic ando- demographic variables, and COVID-19 was performed. Our findings revealed that the average, maximum, and minimum temperatures and relative humidity were significantly associated with rates of COVID-19 new cases in most of the sites, while precipitation was significantly associated only in four sites. Additionally, demographic variables such as the number of inhabitants, the percentage of the population aged 60 years and above, the masculinity index, and the GINI index showed a significant correlation with COVID-19 cases. Due to the rapid evolution of the COVID-19 pandemic, these findings provide strong evidence that biomedical, social, and physical sciences should join forces in truly multidisciplinary research that is critically needed in the current state of our region.
publishDate 2023
dc.date.none.fl_str_mv 2023-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/231503
Mantilla Caicedo, Gilma C.; Rusticucci, Matilde Monica; Suli, Solange; Dankiewicz, Verónica; Salvador, Ayala; et al.; Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America; Elsevier; Heliyon; 9; 5; 5-2023; 1-15
2405-8440
CONICET Digital
CONICET
url http://hdl.handle.net/11336/231503
identifier_str_mv Mantilla Caicedo, Gilma C.; Rusticucci, Matilde Monica; Suli, Solange; Dankiewicz, Verónica; Salvador, Ayala; et al.; Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America; Elsevier; Heliyon; 9; 5; 5-2023; 1-15
2405-8440
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.heliyon.2023.e16056
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2405844023032632
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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