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Crowd and environmental management during mass gatherings.

Johansson, A; Batty, M; Hayashi, K; Al Bar, O; Marcozzi, D; Memish, ZA; (2012) Crowd and environmental management during mass gatherings. Lancet Infectious Diseases , 12 (2) 150 - 156. 10.1016/S1473-3099(11)70287-0. Green open access

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Abstract

Crowds are a feature of large cities, occurring not only at mass gatherings but also at routine events such as the journey to work. To address extreme crowding, various computer models for crowd movement have been developed in the past decade, and we review these and show how they can be used to identify health and safety issues. State-of-the-art models that simulate the spread of epidemics operate on a population level, but the collection of fine-scale data might enable the development of models for epidemics that operate on a microscopic scale, similar to models for crowd movement. We provide an example of such simulations, showing how an individual-based crowd model can mirror aggregate susceptible-infected-recovered models that have been the main models for epidemics so far.

Type: Article
Title: Crowd and environmental management during mass gatherings.
Location: US
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/S1473-3099(11)70287-0
Publisher version: http://dx.doi.org/10.1016/S1473-3099(11)70287-0
Language: English
Additional information: This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Computer Simulation, Crowding, Humans, Mass Behavior, Models, Theoretical
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/1355382
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