Characterization of superspreaders movement in a bidirectional corridor using a social force model

Bibliographic Data

ID22077291
AuthorsDramane Sam Idris Kanté (0000-0002-6148-5713, Cadi Ayyad University, corresponding author), Aissam Jebrane (0000-0001-9479-0039), Abdelilah Hakim (0009-0000-8415-0716, Cadi Ayyad University), Adnane Boukamel
Year2023
Volume11
Pages1188732-1188732
Publication date2023-07-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1188732
PMID37575110
OpenAlexW4385349971
LanguageEN
References cited93

During infectious disease outbreaks, some infected individuals may spread the disease widely and amplify risks in the community. People whose daily activities bring them in close proximity to many others can unknowingly become superspreaders . The use of contact tracking based on social networks, GPS, or mobile tracking data can help to identify superspreaders and break the chain of transmission. We propose a model that aims at providing insight into risk factors of superspreading events. Here, we use a social force model to estimate the superspreading potential of individuals walking in a bidirectional corridor. First, we applied the model to identify parameters that favor exposure to an infectious person in scattered crowds. We find that low walking speed and high body mass both increase the expected number of close exposures. Panic events exacerbate the risks while social distancing reduces both the number and duration of close encounters. Further, in dense crowds, pedestrians interact more and cannot easily maintain the social distance between them. The number of exposures increases with the density of person in the corridor. The study of movements reveals that individuals walking toward the center of the corridor tend to rotate and zigzag more than those walking along the edges, and thus have higher risks of superspreading. The corridor model can be applied to designing risk reduction measures for specific high volume venues, including transit stations, stadiums, and schools

Acoustics · Nanotechnology · Pedestrian · Physics · Social force model · Transport engineering · Computer Science · Engineering · Evacuation and Crowd Dynamics · Materials Science · Traffic and Road Safety · Traffic control and management

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