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2022 | OriginalPaper | Buchkapitel

Using Agent-Based Modelling to Understand Advantageous Behaviours Against COVID-19 Transmission in the Built Environment

verfasst von : Arnaud Grignard, Tri Nguyen-Huu, Patrick Taillandier, Luis Alonso, Nicolas Ayoub, Markus Elkatsha, Gamaliel Palomo, Monica Gomez, Mario Siller, Mayra Gamboa, Carlos Ivan Moreno, Kent Larson

Erschienen in: Multi-Agent-Based Simulation XXII

Verlag: Springer International Publishing

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Abstract

The global Covid-19 pandemic has raised many questions about how we occupy and move in the built environment. Interior environments have been increasingly discussed in numerous studies highlighting how interior spaces play a key role in the spread of pandemics. One societal challenge is to find short-term strategies to reopen indoor venues. Most current approaches focus on an individual’s behavior (maintaining social distance, wearing face masks, and washing their hands) and government policies (confinement, curfew, quarantine, etc.). However, few studies have been conducted to understand a building’s interior where most transmission takes place. How will the utilization of existing interior spaces be improved above and beyond universally applied criteria, while minimizing the risk of disease transmission? This article presents an agent-based model that examines disease transmission risks in various “interior types” in combination with user behaviors and their mobility, as well as three types of transmission vectors (direct, airborne and via surfaces). The model also integrates numerous policy interventions, including wearing masks, hand washing, and the possibility of easily modifying the organization of spaces. Different studies at various scales were conducted both on the University of Guadalajara (UdeG) campus as well as at the MIT Media Lab to illustrate the application of this model.

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Metadaten
Titel
Using Agent-Based Modelling to Understand Advantageous Behaviours Against COVID-19 Transmission in the Built Environment
verfasst von
Arnaud Grignard
Tri Nguyen-Huu
Patrick Taillandier
Luis Alonso
Nicolas Ayoub
Markus Elkatsha
Gamaliel Palomo
Monica Gomez
Mario Siller
Mayra Gamboa
Carlos Ivan Moreno
Kent Larson
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-030-94548-0_7

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