Studying the dynamics of crowd panic propagation during emergency evacuation
Casualties during emergency evacuations are often attributed to people’s panic-driven extreme behaviors rather than the accidents themselves. The propagation of panic is influenced by various factors. Based on the susceptible–infectious–recovered–susceptible (SIRS) model, a system dynamics (SD) mode...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-12-01
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| Series: | Journal of Safety Science and Resilience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666449625000337 |
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| author | Yushan Li Changchun Liu Yi Yang |
| author_facet | Yushan Li Changchun Liu Yi Yang |
| author_sort | Yushan Li |
| collection | DOAJ |
| description | Casualties during emergency evacuations are often attributed to people’s panic-driven extreme behaviors rather than the accidents themselves. The propagation of panic is influenced by various factors. Based on the susceptible–infectious–recovered–susceptible (SIRS) model, a system dynamics (SD) model was developed using AnyLogic software to investigate the spread of panic emotions within a population. A case study focused on hospital emergency evacuations was conducted, wherein factors influencing panic propagation were divided into individual and group levels. The population was classified into three categories—staff, caregivers, and patients—and the effect of the ratio of these categories on evacuation efficiency was examined. Based on these classifications, an evacuation simulation experiment was conducted to examine the effects of panic emotions on evacuation efficiency. Results indicate that optimal hospital evacuation efficiency is achieved with a staff:caregiver:patient ratio of 2:2:1. The overall evacuation process is significantly impacted by panic, resulting in a 64 % increase in evacuation times when panic propagation is considered compared to scenarios where it is not. Furthermore, the initial 10 s following a disaster were identified as crucial for managing severe panic. Valuable insights for improving emergency evacuation management are provided by this study. |
| format | Article |
| id | doaj-art-054e7399686f4f769c9d97e2d4ad312e |
| institution | Kabale University |
| issn | 2666-4496 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Safety Science and Resilience |
| spelling | doaj-art-054e7399686f4f769c9d97e2d4ad312e2025-08-20T03:58:21ZengKeAi Communications Co., Ltd.Journal of Safety Science and Resilience2666-44962025-12-016410020710.1016/j.jnlssr.2025.03.001Studying the dynamics of crowd panic propagation during emergency evacuationYushan Li0Changchun Liu1Yi Yang2School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaSchool of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaSchool of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China; College of Safety Science and Engineering, Nanjing Tech University, Nanjing 211816, China; Correspondence author.Casualties during emergency evacuations are often attributed to people’s panic-driven extreme behaviors rather than the accidents themselves. The propagation of panic is influenced by various factors. Based on the susceptible–infectious–recovered–susceptible (SIRS) model, a system dynamics (SD) model was developed using AnyLogic software to investigate the spread of panic emotions within a population. A case study focused on hospital emergency evacuations was conducted, wherein factors influencing panic propagation were divided into individual and group levels. The population was classified into three categories—staff, caregivers, and patients—and the effect of the ratio of these categories on evacuation efficiency was examined. Based on these classifications, an evacuation simulation experiment was conducted to examine the effects of panic emotions on evacuation efficiency. Results indicate that optimal hospital evacuation efficiency is achieved with a staff:caregiver:patient ratio of 2:2:1. The overall evacuation process is significantly impacted by panic, resulting in a 64 % increase in evacuation times when panic propagation is considered compared to scenarios where it is not. Furthermore, the initial 10 s following a disaster were identified as crucial for managing severe panic. Valuable insights for improving emergency evacuation management are provided by this study.http://www.sciencedirect.com/science/article/pii/S2666449625000337Panic propagationEvacuation simulationSystem dynamicsPersonnel categories |
| spellingShingle | Yushan Li Changchun Liu Yi Yang Studying the dynamics of crowd panic propagation during emergency evacuation Journal of Safety Science and Resilience Panic propagation Evacuation simulation System dynamics Personnel categories |
| title | Studying the dynamics of crowd panic propagation during emergency evacuation |
| title_full | Studying the dynamics of crowd panic propagation during emergency evacuation |
| title_fullStr | Studying the dynamics of crowd panic propagation during emergency evacuation |
| title_full_unstemmed | Studying the dynamics of crowd panic propagation during emergency evacuation |
| title_short | Studying the dynamics of crowd panic propagation during emergency evacuation |
| title_sort | studying the dynamics of crowd panic propagation during emergency evacuation |
| topic | Panic propagation Evacuation simulation System dynamics Personnel categories |
| url | http://www.sciencedirect.com/science/article/pii/S2666449625000337 |
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