A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination
- Autores
- Aguiar, Maíra; Dosi, Giovanni; Knopoff, Damián Alejandro; Virgillito, Maria Enrica
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Lockdown and vaccination policies have been the major concern in the last year in order to contain the SARS-CoV-2 infection during the COVID-19 pandemic. In this paper, we present a model able to evaluate alternative lockdown policies and vaccination strategies. Our approach integrates and refines the multiscale model proposed by Bellomo et al., 2020, analyzing alternative network structures and bridging two perspectives to study complexity of living systems. Inside different matrices of contacts we explore the impact of closures of distinct nodes upon the overall contagion dynamics. Social distancing is shown to be more effective when targeting the reduction of contacts among and inside the most vulnerable nodes, namely hospitals/nursing homes. Moreover, our results suggest that school closures alone would not significantly affect the infection dynamics and the number of deaths in the population. Finally, we investigate a scenario with immunization in order to understand the effectiveness of targeted vaccination policies towards the most vulnerable individuals. Our model agrees with the current proposed vaccination strategy prioritizing the most vulnerable segment of the population to reduce severe cases and deaths.
Fil: Aguiar, Maíra. Università Di Trento; Italia. Basque Center For Applied Mathematics (bcam); España. Ikerbasque, Basque Foundation For Science; España
Fil: Dosi, Giovanni. Sant'anna Scuola Universitaria Superiore Pisa; Italia
Fil: Knopoff, Damián Alejandro. Universidad Nacional de Córdoba; Argentina. Basque Center For Applied Mathematics; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina
Fil: Virgillito, Maria Enrica. Sant'anna Scuola Universitaria Superiore Pisa; Italia - Materia
-
ACTIVE PARTICLES
COVID-19
EPIDEMIOLOGICAL MODELS
HEALTH POLICIES
KINETIC THEORY
NETWORKS
PANDEMIC
SPATIAL PATTERNS
VACCINATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/172725
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A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccinationAguiar, MaíraDosi, GiovanniKnopoff, Damián AlejandroVirgillito, Maria EnricaACTIVE PARTICLESCOVID-19EPIDEMIOLOGICAL MODELSHEALTH POLICIESKINETIC THEORYNETWORKSPANDEMICSPATIAL PATTERNSVACCINATIONhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Lockdown and vaccination policies have been the major concern in the last year in order to contain the SARS-CoV-2 infection during the COVID-19 pandemic. In this paper, we present a model able to evaluate alternative lockdown policies and vaccination strategies. Our approach integrates and refines the multiscale model proposed by Bellomo et al., 2020, analyzing alternative network structures and bridging two perspectives to study complexity of living systems. Inside different matrices of contacts we explore the impact of closures of distinct nodes upon the overall contagion dynamics. Social distancing is shown to be more effective when targeting the reduction of contacts among and inside the most vulnerable nodes, namely hospitals/nursing homes. Moreover, our results suggest that school closures alone would not significantly affect the infection dynamics and the number of deaths in the population. Finally, we investigate a scenario with immunization in order to understand the effectiveness of targeted vaccination policies towards the most vulnerable individuals. Our model agrees with the current proposed vaccination strategy prioritizing the most vulnerable segment of the population to reduce severe cases and deaths.Fil: Aguiar, Maíra. Università Di Trento; Italia. Basque Center For Applied Mathematics (bcam); España. Ikerbasque, Basque Foundation For Science; EspañaFil: Dosi, Giovanni. Sant'anna Scuola Universitaria Superiore Pisa; ItaliaFil: Knopoff, Damián Alejandro. Universidad Nacional de Córdoba; Argentina. Basque Center For Applied Mathematics; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; ArgentinaFil: Virgillito, Maria Enrica. Sant'anna Scuola Universitaria Superiore Pisa; ItaliaWorld Scientific2021-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/172725Aguiar, Maíra; Dosi, Giovanni; Knopoff, Damián Alejandro; Virgillito, Maria Enrica; A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination; World Scientific; Mathematical Models And Methods In Applied Sciences; 31; 12; 11-2021; 2425-24540218-2025CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1142/S0218202521500524info:eu-repo/semantics/altIdentifier/url/https://www.worldscientific.com/doi/abs/10.1142/S0218202521500524info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:42:37Zoai:ri.conicet.gov.ar:11336/172725instacron: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:34982025-09-29 10:42:37.735CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
title |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
spellingShingle |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination Aguiar, Maíra ACTIVE PARTICLES COVID-19 EPIDEMIOLOGICAL MODELS HEALTH POLICIES KINETIC THEORY NETWORKS PANDEMIC SPATIAL PATTERNS VACCINATION |
title_short |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
title_full |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
title_fullStr |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
title_full_unstemmed |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
title_sort |
A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination |
dc.creator.none.fl_str_mv |
Aguiar, Maíra Dosi, Giovanni Knopoff, Damián Alejandro Virgillito, Maria Enrica |
author |
Aguiar, Maíra |
author_facet |
Aguiar, Maíra Dosi, Giovanni Knopoff, Damián Alejandro Virgillito, Maria Enrica |
author_role |
author |
author2 |
Dosi, Giovanni Knopoff, Damián Alejandro Virgillito, Maria Enrica |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
ACTIVE PARTICLES COVID-19 EPIDEMIOLOGICAL MODELS HEALTH POLICIES KINETIC THEORY NETWORKS PANDEMIC SPATIAL PATTERNS VACCINATION |
topic |
ACTIVE PARTICLES COVID-19 EPIDEMIOLOGICAL MODELS HEALTH POLICIES KINETIC THEORY NETWORKS PANDEMIC SPATIAL PATTERNS VACCINATION |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Lockdown and vaccination policies have been the major concern in the last year in order to contain the SARS-CoV-2 infection during the COVID-19 pandemic. In this paper, we present a model able to evaluate alternative lockdown policies and vaccination strategies. Our approach integrates and refines the multiscale model proposed by Bellomo et al., 2020, analyzing alternative network structures and bridging two perspectives to study complexity of living systems. Inside different matrices of contacts we explore the impact of closures of distinct nodes upon the overall contagion dynamics. Social distancing is shown to be more effective when targeting the reduction of contacts among and inside the most vulnerable nodes, namely hospitals/nursing homes. Moreover, our results suggest that school closures alone would not significantly affect the infection dynamics and the number of deaths in the population. Finally, we investigate a scenario with immunization in order to understand the effectiveness of targeted vaccination policies towards the most vulnerable individuals. Our model agrees with the current proposed vaccination strategy prioritizing the most vulnerable segment of the population to reduce severe cases and deaths. Fil: Aguiar, Maíra. Università Di Trento; Italia. Basque Center For Applied Mathematics (bcam); España. Ikerbasque, Basque Foundation For Science; España Fil: Dosi, Giovanni. Sant'anna Scuola Universitaria Superiore Pisa; Italia Fil: Knopoff, Damián Alejandro. Universidad Nacional de Córdoba; Argentina. Basque Center For Applied Mathematics; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina Fil: Virgillito, Maria Enrica. Sant'anna Scuola Universitaria Superiore Pisa; Italia |
description |
Lockdown and vaccination policies have been the major concern in the last year in order to contain the SARS-CoV-2 infection during the COVID-19 pandemic. In this paper, we present a model able to evaluate alternative lockdown policies and vaccination strategies. Our approach integrates and refines the multiscale model proposed by Bellomo et al., 2020, analyzing alternative network structures and bridging two perspectives to study complexity of living systems. Inside different matrices of contacts we explore the impact of closures of distinct nodes upon the overall contagion dynamics. Social distancing is shown to be more effective when targeting the reduction of contacts among and inside the most vulnerable nodes, namely hospitals/nursing homes. Moreover, our results suggest that school closures alone would not significantly affect the infection dynamics and the number of deaths in the population. Finally, we investigate a scenario with immunization in order to understand the effectiveness of targeted vaccination policies towards the most vulnerable individuals. Our model agrees with the current proposed vaccination strategy prioritizing the most vulnerable segment of the population to reduce severe cases and deaths. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-11 |
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/11336/172725 Aguiar, Maíra; Dosi, Giovanni; Knopoff, Damián Alejandro; Virgillito, Maria Enrica; A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination; World Scientific; Mathematical Models And Methods In Applied Sciences; 31; 12; 11-2021; 2425-2454 0218-2025 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/172725 |
identifier_str_mv |
Aguiar, Maíra; Dosi, Giovanni; Knopoff, Damián Alejandro; Virgillito, Maria Enrica; A multiscale network-based model of contagion dynamics: Heterogeneity, spatial distancing and vaccination; World Scientific; Mathematical Models And Methods In Applied Sciences; 31; 12; 11-2021; 2425-2454 0218-2025 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1142/S0218202521500524 info:eu-repo/semantics/altIdentifier/url/https://www.worldscientific.com/doi/abs/10.1142/S0218202521500524 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
World Scientific |
publisher.none.fl_str_mv |
World Scientific |
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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13.070432 |