Gholamreza Khademipour1, Nouzar Nakhaee2, Seyed Mohammad Saberi Anari1, Maryam Sadeghi3, Hojjat Ebrahimnejad4, Hojjat Sheikhbardsiri5. 1. 1Department of Emergency Management Center,Kerman University of Medical Sciences,Kerman,Iran. 2. 2Neuroscience Research Center,Kerman University of Medical Sciences,Kerman,Iran. 3. 3Department of Environmental Health,Kerman University of Medical Sciences,Kerman,Iran. 4. 4Department of Development and Resource Management,Kerman University of Medical Sciences,Kerman,Iran. 5. 5Health Management and Economic Research Center,Isfahan University of Medical Sciences,Isfahan,Iran.
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 $\,s\,{\equals}\,\sqrt {{{L{\vskip -1.5pt \,\,\asterisk\,\,}M} \over {3600}}} $ 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).
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 $\,s\,{\equals}\,\sqrt {{{L{\vskip -1.5pt \,\,\asterisk\,\,}M} \over {3600}}} $ 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).
Entities:
Keywords:
critical density point; emergency; simulation
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