Typical movement behavior at large events increases risk of spreading infectious diseases
- Date:
- September 15, 2022
- Source:
- Universiteit van Amsterdam
- Summary:
- What is the typical movement behavior of visitors to large events, such as concerts, and what does this mean for the risk of spreading infectious diseases like COVID-19? Researchers set out to investigate using data from events in a large stadium in Amsterdam.
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What is the typical movement behaviour of visitors to large events, such as concerts, and what does this mean for the risk of spreading infectious diseases like COVID-19? A group of researchers from the Informatics Institute at the University of Amsterdam, together with an epidemiologist from the Utrecht University, set out to investigate using data from events in a large stadium in Amsterdam. Their results have now been published in the journal Nature Scientific Reports.
Following the outbreak of the COVID-19 pandemic, governments around the world responded with social distancing measures including the cancellation of events involving the gathering of large crowds. Although it is intuitively clear that crowded events present a high level of risk for the spread of an infectious disease like COVID-19, a lot depends on specifically how people move in crowds. Despite a large body of scientific research on both crowd dynamics and human mobility in the past decades, surprisingly little is known about human movement in the specific context of large, crowded events.
Intermittent pattern
As the pandemic was beginning, a small group of researchers from the Informatics Institute were finalising their analyses of movement patterns of visitors to large sports and dance events in the Johan Cruijff stadium in Amsterdam. In two separate publications, they investigate the movement patterns in terms of both space and time. The first of these two publications appeared in February 2021 and compared the movements of individuals in the crowd to the typical foraging patterns that were also present in our human hunter-gatherer ancestors.
Most importantly, they found that individuals were not constantly on the move. People stay in one place for some time, and then decide to go somewhere else, usually in one continuous effort. This leads to an intermittent pattern of movement and rest which is sometimes called 'bursty' in the scientific literature. This observation only comes about when people's movements are studied over longer time spans, e.g. several hours.
Infection risks
The researchers realised that the movement patterns they had observed would have important consequences for the spread of a disease like COVID-19. They then collaborated with theoretical epidemiologist Hans Heesterbeek of Utrecht University. In the team's new publication they reproduce the observed movement behaviour in so-called random walk models, on which they simulate the spread of an infectious disease. This second study appeared on 1 September in Nature Scientific Reports.
This new work exposes the perhaps counter-intuitive fact that the observed intermittent movement behaviour presents an increased level of risk compared to higher and more continuous levels of movement. One would expect that the more people move and encounter other people, the more individuals get infected. However, if the infection also needs time to be transmitted (instead of occurring instantly), the fact that people stop and spend time in proximity to each other increases the risk of infection. The first author of the study, PhD candidate Philip Rutten, comments: "This shows that, if the infection probability is time-dependent, an intermittently moving but freely mixing crowd may present the highest level of transmission risk." The researchers emphasise that this type of crowd movement behaviour may be common to various kinds of events, such as music festivals, religious gatherings, and political demonstrations.
Story Source:
Materials provided by Universiteit van Amsterdam. Note: Content may be edited for style and length.
Journal References:
- Philip Rutten, Michael H. Lees, Sander Klous, Hans Heesterbeek, Peter M. A. Sloot. Modelling the dynamic relationship between spread of infection and observed crowd movement patterns at large scale events. Scientific Reports, 2022; 12 (1) DOI: 10.1038/s41598-022-19081-z
- Philip Rutten, Michael H. Lees, Sander Klous, Peter M.A. Sloot. Intermittent and persistent movement patterns of dance event visitors in large sporting venues. Physica A: Statistical Mechanics and its Applications, 2021; 563: 125448 DOI: 10.1016/j.physa.2020.125448
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