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Use of Dimensional Analysis in the X-, Y-, and Z-Axis to Predict Occurrence of Injury in Human Stampede

Published online by Cambridge University Press:  05 July 2019

Abdullah Alhadhira*
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Department of Emergency Medicine, BIDMC, Boston, Massachusetts Harvard Medical School, BostonMassachusetts Johns Hopkins ARAMCO Healthcare, Dhahran, Saudi Arabia
Michael S Molloy
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Emergency Department, Wexford General Hospital, Ireland East Hospital Group, Wexford, Ireland School of Medicine, University College Dublin, Ireland
Marcel Casasola
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Department of Emergency Medicine, BIDMC, Boston, Massachusetts
Ritu R Sarin
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Department of Emergency Medicine, BIDMC, Boston, Massachusetts
Michael Massey
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts
Amalia Voskanyan
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Department of Emergency Medicine, BIDMC, Boston, Massachusetts
G.R. Ciottone
Affiliation:
BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, BIDMC, Boston, Massachusetts Department of Emergency Medicine, BIDMC, Boston, Massachusetts Harvard Medical School, BostonMassachusetts
*
Correspondence and reprint requests to Abdullah A. Alhadhira, BIDMC Fellowship in Disaster Medicine, Department of Emergency Medicine, One Deaconess Road, WCC2, Boston, MA 02215, USA Telephone: +1 (617) 412-0660 (e-mail: [email protected]).

Abstract

Background:

Human stampedes (HS) may result in mass casualty incidents (MCI) that arise due to complex interactions between individuals, collective crowd, and space, which have yet to be described from a physics perspective. HS events were analyzed using basic physics principles to better understand the dynamic kinetic variables that give rise to HS.

Methods:

A literature review was performed of medical and nonmedical sourced databases, Library of Congress databases, and online sources for the term human stampedes resulting in 25,123 references. Filters were applied to exclude nonhuman events. Retrieved references were reviewed for a predefined list of physics terms. Data collection involved recording frequency of each phrase and physics principle to give the final proportions of each predefined principle used a single-entry method for each of the 105 event reports analyzed. Data analysis was performed using the R statistics packages “tidyverse”, “psych”, “lubridate”, and “Hmisc” with descriptive statistics used to describe the frequency of each observed variable.

Results:

Of the 105 reports of HS resulting in injury or death reviewed, the following frequency of terms were found: density change in a limited capacity, 45%; XY-axis motion failure, 100%; loss of proxemics, 100%; deceleration with average velocity of zero, 90%; Z-axis displacement pathology (falls), 92%; associated structure with nozzle effect, 93%; and matched fluid dynamic of high pressure stagnation of mass gathering, 100%.

Conclusions:

Description or reference to principles of physics was seen in differing frequency in 105 reports. These include XY-axis motion failure of deceleration that leads to loss of human to human proxemics, and high stagnation pressure resulting in the Z-axis displacement effect (falls) causing injury and death. Real-time video-analysis monitoring of high capacity events or those with known nozzle effects for loss of proxemics and Z-axis displacement pathology offers the opportunity to prevent mortality from human stampedes.

Type
Concepts in Disaster Medicine
Copyright
© 2019 Society for Disaster Medicine and Public Health, Inc.

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References

REFERENCES

Alotaibi, BS, Molloy, MS, Mechem, CC, et al. Human Stampede. In: Ciottone, GR, Biddinger, PD, Darling, RG, et al., eds. Ciottone’s Disaster Medicine. Amsterdam: Elsevier Health Sciences; 2015:992.Google Scholar
Huang, Y, Xu, T, Sun, W.Public health lesson from Shanghai New Year’s Eve stampede. Iran J Public Health. 2015;44(7):1021-1022.Google ScholarPubMed
Illiyas, FT, Mani, SK, Pradeepkumar, AP, et al. Human stampedes during religious festivals: A comparative review of mass gathering emergencies in India. Int J Disaster Risk Reduct. 2013;5:10-18.Google Scholar
Ngai, KM, Burkle, FM, Hsu, A, et al. Human stampedes: a systematic review of historical and peer-reviewed sources. Disaster Med Public Health Prep. 2013;3(04):191-195.10.1097/DMP.0b013e3181c5b494CrossRefGoogle Scholar
Ali, S, Nishino, K, Manocha, D, et al. Modeling, Simulation and Visual Analysis of Crowds. Berlin: Springer Science & Business Media; 2013:1.Google Scholar
Gao, K.An emergency evacuation model based on computer vision smart inducing in hotel stampede environment. Appl Mech Mater. 2014;556-562:5736-5739.Google Scholar
Jiang, L, Li, J, Shen, C, et al. Obstacle optimization for panic flow–reducing the tangential momentum increases the escape speed. Gao Z-K, editor. PLoS One. 2014;9(12):e115463.10.1371/journal.pone.0115463CrossRefGoogle ScholarPubMed
Piazza, F.Simple Monte Carlo model for crowd dynamics. Phys Rev E Stat Nonlin Soft Matter Phys. 2010;82(2 Pt 2):026111.Google ScholarPubMed
Zhang, Y, Zhang, X, Yuan, LL.Stampede risk recognition for evacuation study using thermodynamic diagram remote sensing. Chem Eng Trans. 2016;51:721-726.Google Scholar
Golas, A, Narain, R, Lin, MC.Continuum modeling of crowd turbulence. Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Oct;90(4):042816.Google ScholarPubMed
Dixon, SL.Fluid Mechanics and Thermodynamics of Turbomachinery. Amsterdam: Elsevier; 1998:1.Google Scholar
Moher, D, Liberati, A, Tetzlaff, J, et al. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ. 2009;339:b2535.Google ScholarPubMed
Young, HD, Freedman, RA.University Physics with Modern Physics Technology Update, Volume 1. Pearson New International Edition. Pearson Higher Ed; 2013:1.Google Scholar
Gill, JR, Landi, K.Traumatic asphyxial deaths due to an uncontrolled crowd. Am J Forensic Med Pathol. 2004;25(4):358-361.Google Scholar
Hsieh, Y-H, Ngai, KM, Burkle, FM, et al. Epidemiological characteristics of human stampedes. Disaster Med Public Health Prep. 2013;3(04):217-223.Google Scholar
Johnson, NR.Panic at “The Who Concert Stampede”: An empirical assessment. Soc Probl. 1987;34(4):362-373.Google Scholar
Madzimbamuto, FD, Madzimbamuto, F.A hospital response to a soccer stadium stampede in Zimbabwe. Emerg Med J. 2003;20(6):556-559.Google ScholarPubMed
Hsu, EB, Burkle, FM.Cambodian Bon Om Touk stampede highlights preventable tragedy. Prehosp Disaster Med. 2012;27(05):481-482.Google ScholarPubMed
Burkle, FM, Hsu, EB.Ram Janki Temple: Understanding human stampedes. Lancet. 2011;377(9760):106-107.Google ScholarPubMed
Greenough, PG.The Kumbh Mela stampede: disaster preparedness must bridge jurisdictions. BMJ. 2013;346:f3254.Google ScholarPubMed
Alaska, YA, Aldawas, AD, Aljerian, NA, et al. The impact of crowd control measures on the occurrence of stampedes during Mass Gatherings: The Hajj experience. Travel Med Infect Dis. 2017;15:67-70.Google ScholarPubMed
Begum, AA.Unnatural deaths during Zakat distribution. Bangladesh Med Res Counc Bull. 1993;19(3):99-102.Google ScholarPubMed
Bhave, G, Neilson, EG.Body fluid dynamics: back to the future. J Am Soc Nephrol. 2011;22(12):2166-2181.Google ScholarPubMed
Still, GK. Six people per square metre. https://www.gkstill.com/Support/crowd-flow/6People.html. Accessed September 27, 2018.Google Scholar
Still, GK. Crowd dynamics. PhD thesis, Math Dep. 2000; (Coventry University, UK):264.Google Scholar
Gómez, RW, Hernandez-Gomez, JJ, Marquina, V.A jumping cylinder on an inclined plane. Eur J Phys. 2012;33. doi: 10.1088/0143-0807/33/5/1359Google Scholar
Yang, Y, Qitai, E, Wang, Q, et al. Development of Two-Dimensional Convergent-Divergent Nozzle Performance Rapidly Analysis Project. Paris, France: Atlantis Press; 2015.Google Scholar
Wardhana, K, Hadipriono, FC.Analysis of recent bridge failures in the United States. J Perform Constr Facil. 2003;17(3):144-150. doi: 10.1061/(ASCE)0887-3828(2003)17:3(144)Google Scholar