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...

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Detalles Bibliográficos
Autores: Singh, David E., Marinescu, Maria Cristina, Guzmán Merino, Miguel, Durán, Christian, Delgado Sanz, Concepción, Gómez Barroso, Diana, Carretero Pérez, Jesús
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/343899
Acceso en línea:https://hdl.handle.net/2117/343899
https://dx.doi.org/10.3389/fpubh.2021.636023
Access Level:acceso abierto
Palabra clave:COVID-19 (Disease)
Epidemics -- Simulation methods
Simulation
Social distancing
Mitigation policies
Face mask
COVID-19 (Malaltia)
Epidèmies -- Mètodes de simulació
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica
Descripción
Sumario: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.