TY - JOUR
T1 - Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area
AU - Singh, David E.
AU - Marinescu, Maria Cristina
AU - Guzmán-Merino, Miguel
AU - Durán, Christian
AU - Delgado-Sanz, Concepción
AU - Gomez-Barroso, Diana
AU - Carretero, Jesus
N1 - Publisher Copyright:
© Copyright © 2021 Singh, Marinescu, Guzmán-Merino, Durán, Delgado-Sanz, Gomez-Barroso and Carretero.
PY - 2021/3/16
Y1 - 2021/3/16
N2 - 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.
AB - 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.
KW - COVID-19
KW - face mask
KW - mitigation policies
KW - simulation
KW - social distancing
UR - http://www.scopus.com/inward/record.url?scp=85103383157&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2021.636023
DO - 10.3389/fpubh.2021.636023
M3 - Article
C2 - 33796497
AN - SCOPUS:85103383157
SN - 2296-2565
VL - 9
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 636023
ER -