The Use of Crowd Models for Risk Analysis During the Covid-19 Pandemic
Ronchi, Enrico LU
; Lovreglio, Ruggiero
LU
; Scozzari, Rugiada
and Fronterrè, Michele
(2024)
In Modeling and Simulation in Science, Engineering and Technology
Part F2950.
p.45-69
- Abstract
The emergence of pandemics like Covid-19 has raised important issues regarding the safe utilisation of spaces due to the potential for virus transmission in both enclosed and open built environments. This chapter explores the challenges posed by pandemics in terms of safe space utilisation, considering the potential virus transmission risks. It presents a risk analysis methodology that makes use of crowd modelling tools to assess safety in relation to pedestrian behaviour. Crowd models offer valuable insights into pedestrian movement within the built environment, making them ideal for proximity analysis. This work identifies necessary modifications to crowd modelling tools to be used during a pandemic. Specifically, suggestions are... (More)
The emergence of pandemics like Covid-19 has raised important issues regarding the safe utilisation of spaces due to the potential for virus transmission in both enclosed and open built environments. This chapter explores the challenges posed by pandemics in terms of safe space utilisation, considering the potential virus transmission risks. It presents a risk analysis methodology that makes use of crowd modelling tools to assess safety in relation to pedestrian behaviour. Crowd models offer valuable insights into pedestrian movement within the built environment, making them ideal for proximity analysis. This work identifies necessary modifications to crowd modelling tools to be used during a pandemic. Specifically, suggestions are provided to enhance crowd modelling outputs and their applicability during pandemics. This chapter also presents practical solutions for space utilisation by employing a risk evaluation based on proximity analysis and exposure assessment to ensure human safety. By considering these insights, design and management solutions can be identified to effectively reduce the risk of virus transmission in indoor and outdoor settings.
(Less)
- author
- Ronchi, Enrico
LU
; Lovreglio, Ruggiero
LU
; Scozzari, Rugiada
and Fronterrè, Michele
- organization
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Covid-19, Crowd dynamics, Crowd management, Crowd model, Proximity analysis
- host publication
- Modeling and Simulation in Science, Engineering and Technology
- series title
- Modeling and Simulation in Science, Engineering and Technology
- volume
- Part F2950
- pages
- 25 pages
- publisher
- Birkhäuser
- external identifiers
-
- scopus:85198335324
- ISSN
- 2164-3679
- 2164-3725
- DOI
- 10.1007/978-3-031-56794-0_3
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
- id
- a4f1aa5f-81a3-4f6f-8782-557764476c3d
- date added to LUP
- 2024-11-27 11:04:25
- date last changed
- 2025-06-12 02:47:42
@inbook{a4f1aa5f-81a3-4f6f-8782-557764476c3d,
abstract = {{<p>The emergence of pandemics like Covid-19 has raised important issues regarding the safe utilisation of spaces due to the potential for virus transmission in both enclosed and open built environments. This chapter explores the challenges posed by pandemics in terms of safe space utilisation, considering the potential virus transmission risks. It presents a risk analysis methodology that makes use of crowd modelling tools to assess safety in relation to pedestrian behaviour. Crowd models offer valuable insights into pedestrian movement within the built environment, making them ideal for proximity analysis. This work identifies necessary modifications to crowd modelling tools to be used during a pandemic. Specifically, suggestions are provided to enhance crowd modelling outputs and their applicability during pandemics. This chapter also presents practical solutions for space utilisation by employing a risk evaluation based on proximity analysis and exposure assessment to ensure human safety. By considering these insights, design and management solutions can be identified to effectively reduce the risk of virus transmission in indoor and outdoor settings.</p>}},
author = {{Ronchi, Enrico and Lovreglio, Ruggiero and Scozzari, Rugiada and Fronterrè, Michele}},
booktitle = {{Modeling and Simulation in Science, Engineering and Technology}},
issn = {{2164-3679}},
keywords = {{Covid-19; Crowd dynamics; Crowd management; Crowd model; Proximity analysis}},
language = {{eng}},
pages = {{45--69}},
publisher = {{Birkhäuser}},
series = {{Modeling and Simulation in Science, Engineering and Technology}},
title = {{The Use of Crowd Models for Risk Analysis During the Covid-19 Pandemic}},
url = {{http://dx.doi.org/10.1007/978-3-031-56794-0_3}},
doi = {{10.1007/978-3-031-56794-0_3}},
volume = {{Part F2950}},
year = {{2024}},
}