Crowd Simulations and Determining the Critical Density Point of Emergency Situations

Crowd Simulations and Determining the Critical Density Point of Emergency Situations Publisher Pubmed

Khademipour G¹ ; Nakhaee N² ; Anari SMS¹ ; Sadeghi M³ ; Ebrahimnejad H⁴ ; Sheikhbardsiri H⁵

Show Affiliations

1. Department of Emergency Management Center, Kerman University of Medical Sciences, Kerman, Iran
2. Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran
3. Department of Environmental Health, Kerman University of Medical Sciences, Kerman, Iran
4. Department of Development and Resource Management, Kerman University of Medical Sciences, Kerman, Iran
5. Department of Health Services Administration, Health Management and Economic Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Disaster Medicine and Public Health Preparedness Published:2017

Abstract

Objective In modern societies, crowds and mass gatherings are recurrent. A combination of inadequate facilities and inefficient population management can lead to injury and death. Simulating people's behavior in crowds and mass gatherings can assist in the planning and management of gatherings, especially in emergency situations. Methods We aimed to determine the crowd pattern and the critical density point in the grand bazaar of Kerman in Iran. We collected data by use of a census method with a questionnaire. To determine the critical density point, height and weight data were placed in the equation and the outer body surface of all the individuals in the bazaar was calculated. The crowd was simulated by use of flow-based modeling. Flow rate was determined by using the equation (flow rate=density ∗ speed). By use of SketchUp Pro software (version 8; Trimble, Sunnyvale, CA), the movement of each person and the general flow rate were simulated in the three-dimensional environment of Kerman bazaar. Results Our findings showed that the population critical density point in Kerman bazaar would be 6112 people. In an accident, the critical density point in Kerman bazaar would be created in about 1 minute 10 seconds after the event. Conclusion It seems necessary to identify and provide solutions for reducing the risk of disasters caused by overcrowding in Kerman bazaar. It is suggested that researchers conduct studies to design safe and secure emergency evacuation of Kerman bazaar as well as proper planning for better and faster access of aid squads to this location. (Disaster Med Public Health Preparedness. 2017;11:674-680) . Copyright © 2017 Society for Disaster Medicine and Public Health, Inc.

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Style	Citing Format
MLA	Khademipour G, et al.. "Crowd Simulations and Determining the Critical Density Point of Emergency Situations." Disaster Medicine and Public Health Preparedness, vol. 11, no. 6, 2017, pp. 674-680.
APA	Khademipour G, Nakhaee N, Anari SMS, Sadeghi M, Ebrahimnejad H, Sheikhbardsiri H (2017). Crowd Simulations and Determining the Critical Density Point of Emergency Situations. Disaster Medicine and Public Health Preparedness, 11(6), 674-680.
Chicago	Khademipour G, Nakhaee N, Anari SMS, Sadeghi M, Ebrahimnejad H, Sheikhbardsiri H. "Crowd Simulations and Determining the Critical Density Point of Emergency Situations." Disaster Medicine and Public Health Preparedness 11, no. 6 (2017): 674-680.
Harvard	Khademipour G et al. (2017) 'Crowd Simulations and Determining the Critical Density Point of Emergency Situations', Disaster Medicine and Public Health Preparedness, 11(6), pp. 674-680.
Vancouver	Khademipour G, Nakhaee N, Anari SMS, Sadeghi M, Ebrahimnejad H, Sheikhbardsiri H. Crowd Simulations and Determining the Critical Density Point of Emergency Situations. Disaster Medicine and Public Health Preparedness. 2017;11(6):674-680.
BibTex	@article{ author = {Khademipour G and Nakhaee N and Anari SMS and Sadeghi M and Ebrahimnejad H and Sheikhbardsiri H}, title = {Crowd Simulations and Determining the Critical Density Point of Emergency Situations}, journal = {Disaster Medicine and Public Health Preparedness}, volume = {11}, number = {6}, pages = {674-680}, year = {2017} }
RIS	TY - JOUR AU - Khademipour G AU - Nakhaee N AU - Anari SMS AU - Sadeghi M AU - Ebrahimnejad H AU - Sheikhbardsiri H TI - Crowd Simulations and Determining the Critical Density Point of Emergency Situations JO - Disaster Medicine and Public Health Preparedness VL - 11 IS - 6 SP - 674 EP - 680 PY - 2017 ER -

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