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Use of Predictive Modeling to Plan for Special Event Medical Care During Mass Gathering Events

Published online by Cambridge University Press:  06 June 2019

Rachel L. Allgaier ,
Nina Shaafi-Kabiri ,
Carla A. Romney ,
Lee A. Wallis ,
John Joseph Burke ,
Jaspreet Bhangu  and
Kevin C. Thomas
Rachel L. Allgaier
Affiliation:
Division of Emergency Medicine, Department of Family and Emergency Medicine, Stellenbosch University, Cape Town, South Africa
Nina Shaafi-Kabiri
Affiliation:
Laboratory for Human Neurobiology, Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
Carla A. Romney
Affiliation:
Department of Medical Sciences & Education, Boston University School of Medicine, Boston, MA
Lee A. Wallis
Affiliation:
Division of Emergency Medicine, Department of Family and Emergency Medicine, Stellenbosch University, Cape Town, South Africa
John Joseph Burke
Affiliation:
Laboratory for Human Neurobiology, Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
Jaspreet Bhangu*
Affiliation:
Laboratory for Human Neurobiology, Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
Kevin C. Thomas*
Affiliation:
Laboratory for Human Neurobiology, Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
*
Correspondence and reprint requests to Kevin C. Thomas, Boston University School of Medicine, 650 Albany Street, X140, Boston, MA 02118 (e-mail: [email protected]).
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Abstract

Objectives:

In 2010, South Africa (SA) hosted the Fédération Internationale de Football Association (FIFA) World Cup (soccer). Emergency Medical Services (EMS) used the SA mass gathering medicine (MGM) resource model to predict resource allocation. This study analyzed data from the World Cup and compared them with the resource allocation predicted by the SA mass gathering model.

Methods:

Prospectively, data were collected from patient contacts at 9 venues across the Western Cape province of South Africa. Required resources were based on the number of patients seeking basic life support (BLS), intermediate life support (ILS), and advanced life support (ALS). Overall patient presentation rates (PPRs) and transport to hospital rates (TTHRs) were also calculated.

Results:

BLS services were required for 78.4% (n = 1279) of patients and were consistently overestimated using the SA mass gathering model. ILS services were required for 14.0% (n = 228), and ALS services were required for 3.1% (n = 51) of patients. Both ILS and ALS services, and TTHR were underestimated at smaller venues.

Conclusions:

The MGM predictive model overestimated BLS requirements and inconsistently predicted ILS and ALS requirements. MGM resource models, which are heavily based on predicted attendance levels, have inherent limitations, which may be improved by using research-based outcomes.

Keywords

mass gathering medicinepatient transfertriage
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 13 , Issue 5-6 , December 2019 , pp. 874 - 879
Copyright
Copyright © 2019 Society for Disaster Medicine and Public Health, Inc. 

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References

REFERENCES

Arbon, P. Mass-gathering medicine: a review of the evidence and future directions for research. Prehosp Disaster Med. 2007;22(2):131–135.10.1017/S1049023X00004507CrossRefGoogle ScholarPubMed
Baker, WM, Simone, BM, Niemann, JT, Daly, A. Special event medical care: the 1984 Los Angeles Summer Olympics. Ann Emerg Med. 1985;14:515–516.10.1016/S0196-0644(85)80419-4CrossRefGoogle Scholar
Varon, J, Fromm, RE Jr. Critical illness at mass gatherings is uncommon. J Emerg Med. 2003;25(4):409–413.10.1016/j.jemermed.2003.03.001CrossRefGoogle ScholarPubMed
Michael, JA, Barbera, JA. Mass gathering medical care: a twenty-five year review. Prehosp Disaster Med. 1997;12(4):305–312.10.1017/S1049023X00037857CrossRefGoogle ScholarPubMed
Milsten, AM, Seaman, KG, Liu, P, et al. Variables influencing medical usage rates, injury patterns, and levels of care for mass gatherings. Prehosp Disaster Med. 2003;18(4):334–346.10.1017/S1049023X00001291CrossRefGoogle ScholarPubMed
Milsten, AM, Maguire, BJ, Bissell, RA, Seaman, KG. Mass-gathering medical care: a review of the literature. Prehosp Disaster Med. 2002;17(3):151–162.10.1017/S1049023X00000388CrossRefGoogle ScholarPubMed
DeLorenzo, RA. Mass gathering medicine: a review. Prehosp Disaster Med. 1997;12(1):68–72.10.1017/S1049023X00037250CrossRefGoogle Scholar
Zeitz, KM, Tan, HM, Grief, M, et al. Crowd behavior at mass gatherings: a literature review. Prehosp Disaster Med. 2009;24(1):32–38.10.1017/S1049023X00006518CrossRefGoogle ScholarPubMed
Arbon, P, Bridgewater, FHG, Smith, C. Mass gathering medicine: a predictive model for patient presentation and transportation rates. Prehosp Disaster Med. 2001;16(3):109–116.10.1017/S1049023X00025905CrossRefGoogle Scholar
Arbon, P. The development of conceptual models for mass-gathering health. Prehosp Disaster Med. 2004;19(3):208–212.10.1017/S1049023X00001795CrossRefGoogle ScholarPubMed
Calabro, JJ, Rivera-Rivera, EJ, Reich, JJ, et al. Provision of emergency medical care for crowds. Irving, TX: American College of Emergency Physicians EMS Committee; 1995–1996.Google Scholar
Flabouris, A, Bridgewater, F. An analysis of demand for first-aid care at a major public event. Prehosp Disaster Med. 1996;11(1):48–54.10.1017/S1049023X00042345CrossRefGoogle Scholar
Green, GB, Burnham, G. Health care at mass gatherings. J Am Med Assoc. 1998;279(18):1485–1486.10.1001/jama.279.18.1485CrossRefGoogle ScholarPubMed
Health and Safety Executive. The event safety guide. A guide to health, safety and welfare at music and similar events. London: Her Majesty’s Stationery Office; 1999.Google Scholar
Smith, W. Medical resource model for mass gatherings [Dissertation]; 2008.Google Scholar
Ranse, J, Hutton, A, Keene, T, et al. Health service impact from mass gatherings: a systematic literature review. Prehosp Disaster Med. 2017;32(1):71–77.10.1017/S1049023X16001199CrossRefGoogle ScholarPubMed
Hardcastle, TC, Naidoo, M, Samlal, S, et al. The Moses Mabhida medical plan: medical care planning and execution at a FIFA 2010 stadium; the Durban experience. Open Access Emerg Med. 2010;2:91–97.10.2147/OAEM.S14899CrossRefGoogle Scholar
Bhangu, A, Agar, C, Pickard, L, Leary, A. The Villa Park experience: crowd consultations at an English Premiership football stadium, season 2007–8. Emerg Med J. 2010;27(6):424–429.10.1136/emj.2009.078170CrossRefGoogle ScholarPubMed
Leonard, RB, Nuji, EK, Petrilli, R, Calabro, JJ. Provision of emergency medical care for crowds. [Information Paper]. Irving, TX: American College of Emergency Physicians; 1990.Google Scholar
Locoh-Donou, S, Yan, G, Berry, T, et al. Mass gathering medicine: event factors predicting patient presentation rates. Intern Emerg Med. 2016;11(5):745–752.10.1007/s11739-015-1387-1CrossRefGoogle ScholarPubMed
Perron, AD, Brady, WJ, Custalow, CB, Johnson, DM. Association of heat index and patient volume at a mass gathering event. Prehosp Emerg Care. 2005;9(1):49–52.10.1080/10903120590891976CrossRefGoogle Scholar