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Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area
This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. Epi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007867/ https://www.ncbi.nlm.nih.gov/pubmed/33796497 http://dx.doi.org/10.3389/fpubh.2021.636023 |
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author | Singh, David E. Marinescu, Maria-Cristina Guzmán-Merino, Miguel Durán, Christian Delgado-Sanz, Concepción Gomez-Barroso, Diana Carretero, Jesus |
author_facet | Singh, David E. Marinescu, Maria-Cristina Guzmán-Merino, Miguel Durán, Christian Delgado-Sanz, Concepción Gomez-Barroso, Diana Carretero, Jesus |
author_sort | Singh, David E. |
collection | PubMed |
description | This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. EpiGraph implements a social interaction model, which realistically captures a large number of characteristics of individuals and groups, as well as their individual interconnections, which are extracted from connection patterns in social networks. Besides the epidemiological and social interaction components, it also models people's short and long-distance movements as part of a transportation model. These features, together with the capacity to simulate scenarios with millions of individuals and apply different contention and mitigation measures, gives EpiGraph the potential to reproduce the COVID-19 evolution and study medium-term effects of the virus when applying mitigation methods. EpiGraph, obtains closely aligned infected and death curves related to the first wave in the Madrid metropolitan area, achieving similar seroprevalence values. We also show that selective lockdown for people over 60 would reduce the number of deaths. In addition, evaluate the effect of the use of face masks after the first wave, which shows that the percentage of people that comply with mask use is a crucial factor for mitigating the infection's spread. |
format | Online Article Text |
id | pubmed-8007867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80078672021-03-31 Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area Singh, David E. Marinescu, Maria-Cristina Guzmán-Merino, Miguel Durán, Christian Delgado-Sanz, Concepción Gomez-Barroso, Diana Carretero, Jesus Front Public Health Public Health This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. EpiGraph implements a social interaction model, which realistically captures a large number of characteristics of individuals and groups, as well as their individual interconnections, which are extracted from connection patterns in social networks. Besides the epidemiological and social interaction components, it also models people's short and long-distance movements as part of a transportation model. These features, together with the capacity to simulate scenarios with millions of individuals and apply different contention and mitigation measures, gives EpiGraph the potential to reproduce the COVID-19 evolution and study medium-term effects of the virus when applying mitigation methods. EpiGraph, obtains closely aligned infected and death curves related to the first wave in the Madrid metropolitan area, achieving similar seroprevalence values. We also show that selective lockdown for people over 60 would reduce the number of deaths. In addition, evaluate the effect of the use of face masks after the first wave, which shows that the percentage of people that comply with mask use is a crucial factor for mitigating the infection's spread. Frontiers Media S.A. 2021-03-16 /pmc/articles/PMC8007867/ /pubmed/33796497 http://dx.doi.org/10.3389/fpubh.2021.636023 Text en Copyright © 2021 Singh, Marinescu, Guzmán-Merino, Durán, Delgado-Sanz, Gomez-Barroso and Carretero. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Singh, David E. Marinescu, Maria-Cristina Guzmán-Merino, Miguel Durán, Christian Delgado-Sanz, Concepción Gomez-Barroso, Diana Carretero, Jesus Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title | Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title_full | Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title_fullStr | Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title_full_unstemmed | Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title_short | Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area |
title_sort | simulation of covid-19 propagation scenarios in the madrid metropolitan area |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007867/ https://www.ncbi.nlm.nih.gov/pubmed/33796497 http://dx.doi.org/10.3389/fpubh.2021.636023 |
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