Analytical modelling of the spread of disease in confined and crowded spaces

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

Media Type:

Electronic Article

Year of Publication:

2014

Contained In:

Scientific reports - Vol. 4 (2014), p. 4856

Language:

English

Contributors:

Goscé, Lara
Barton, David A W
Johansson, Anders

Links:

Volltext

Keywords:

Crowding
Disease
Environment
Humans
Journal Article
Kinetics
Models, Biological

Notes:

Date Completed 22.10.2015

Date Revised 13.11.2018

published: Electronic

Citation Status MEDLINE

Copyright: From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Physical Description:

Online-Ressource

doi:

10.1038/srep04856

PMID:

24798322

PPN (Catalogue-ID):

NLM237908875