Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area

David E. Singh, Maria Cristina Marinescu, Miguel Guzmán-Merino, Christian Durán, Concepción Delgado-Sanz, Diana Gomez-Barroso, Jesus Carretero

Research output: Indexed journal article Articlepeer-review

15 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number636023
JournalFrontiers in Public Health
Volume9
DOIs
Publication statusPublished - 16 Mar 2021
Externally publishedYes

Keywords

  • COVID-19
  • face mask
  • mitigation policies
  • simulation
  • social distancing

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