Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-27T22:42:21.868Z Has data issue: false hasContentIssue false
  • English
  • Français

Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings

Published online by Cambridge University Press:  17 November 2014

Adam Lund ,
Sheila A. Turris ,
Ron Bowles ,
Malinda Steenkamp ,
Alison Hutton ,
Jamie Ranse  and
Paul Arbon
Adam Lund*
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada Justice Institute of British Columbia, New Westminster, British Columbia, Canada
Sheila A. Turris
Affiliation:
Justice Institute of British Columbia, New Westminster, British Columbia, Canada Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada School of Nursing, University of Victoria, Victoria, British Columbia, Canada
Ron Bowles
Affiliation:
Justice Institute of British Columbia, New Westminster, British Columbia, Canada
Malinda Steenkamp
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Consequence/High Visibility Events, Flinders University of South Australia, Adelaide, South Australia, Australia
Alison Hutton
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Consequence/High Visibility Events, Flinders University of South Australia, Adelaide, South Australia, Australia
Jamie Ranse
Affiliation:
University of Canberra, Faculty of Health, Bruce, Australian Capital Territory, Australia
Paul Arbon
Affiliation:
Flinders University, World Health Organization Collaborating Centre for Mass Gatherings and High Consequence/High Visibility Events, Flinders University of South Australia, Adelaide, South Australia, Australia
*
Correspondence: Adam Lund, MD, FRCPC Emergency Department Royal Columbian Hospital 330 East Columbia Street New Westminster, British Columbia, V3L 3W7, Canada E-mail [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

The science underpinning the study of mass-gathering health (MGH) is developing rapidly. Current knowledge fails to adequately inform the understanding of the science of mass gatherings (MGs) because of the lack of theory development and adequate conceptual analysis. Defining populations of interest in the context of MGs is required to permit meaningful comparison and meta-analysis between events.

Process

A critique of existing definitions and descriptions of MGs was undertaken. Analyzing gaps in current knowledge, the authors sought to delineate the populations affected by MGs, employing a consensus approach to formulating a population model. The proposed conceptual model evolved through face-to-face group meetings, structured breakout sessions, asynchronous collaboration, and virtual international meetings.

Findings and Interpretation

Reporting on the incidence of health conditions at specific MGs, and comparing those rates between and across events, requires a common understanding of the denominators, or the total populations in question. There are many, nested populations to consider within a MG, such as the population of patients, the population of medical services providers, the population of attendees/audience/participants, the crew, contractors, staff, and volunteers, as well as the population of the host community affected by, but not necessarily attending, the event.

A pictorial representation of a basic population model was generated, followed by a more complex representation, capturing a global-health perspective, as well as academically- and operationally-relevant divisions in MG populations.

Conclusions

Consistent definitions of MG populations will support more rigorous data collection. This, in turn, will support meta-analysis and pooling of data sources internationally, creating a foundation for risk assessment as well as illness and injury prediction modeling. Ultimately, more rigorous data collection will support methodology for evaluating health promotion, harm reduction, and clinical-response interventions at MGs. Delineating MG populations progresses the current body of knowledge of MGs and informs the understanding of the full scope of their health effects.

LundA , TurrisSA , BowlesR , SteenkampM , HuttonA , RanseJ , ArbonP . Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings. Prehosp Disaster Med. 2014;29(6):1-7.

Keywords

mass gatheringsmass-gathering healthminimum data setpopulationtheoretical modeling
Type
Special Reports
Information
Prehospital and Disaster Medicine , Volume 29 , Issue 6 , December 2014 , pp. 648 - 654
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Arbon, P. The development of conceptual models for mass-gathering health. Prehosp Disaster Med. 2004;19(2):212-217.Google Scholar
2. Arbon, P, Cusack, L, Verdonk, N. Mass gathering public health and emergency medicine literature review: levels of evidence. Austalasian J of Paramed. 2013;10(1):1-5.Google Scholar
3. Tam, JS, Barbeschi, M, Shapovalova, N, Briand, S, Memish, ZA, Kieny, MP. Research agenda for mass gathering: a call to action. Lancet. 2012;12(2):231-239.CrossRefGoogle ScholarPubMed
4. Ranse, J, Hutton, A. Minimum data set for mass gathering health research and evaluation: a discussion paper. Prehosp Disaster Med. 2012;27(6):1-8.CrossRefGoogle ScholarPubMed
5. Steffen, R, Bouchama, A, Johansson, A, et al. Non-communicable health risks during mass gatherings. Lancet. 2012;12(2):142-149.Google Scholar
6. Turris, SA, Lund, A. Minimum data set for mass-gatherings health research and evaluation: a response. Prehosp Disaster Med. 2013;28(2):191-193.Google Scholar
7. Abubakar, I, Gautret, P, Brumnette, GW, et al. Global perspectives for prevention of infectious diseases associated with mass gatherings. Lancet. 2012;12(2):66-74.Google Scholar
8. CBC News. Popular Pemberton Music Festival Cancelled. http://www.cbc.ca/news/canada/british-columbia/popular-pemberton-music-festival-cancelled-for-2009-1.820216. Accessed March 16, 2014.Google Scholar
9. Medical Risk Classification for Mass Gatherings. Delivering a Healthy WA. http://www.public.health.wa.gov.au/cproot/2542/2/Medical%20Risk%20Classification.pdf. Accessed March 16, 2014.Google Scholar
10. World Health Organization. 2008. Communicable disease alert and response: key considerations. http://www.who.int/csr/Mass_gatherings2.pdf. Accessed March 16, 2014.Google Scholar
11. Lund, A, Turris, SA, Bowles, RR. Conceptualizing the impact of special events on community health service levels: an operational analysis. Prehosp Disaster Med. 2014;29(5):525-532.CrossRefGoogle ScholarPubMed
12. Welch, TR. Emergency department volumes and “mass events.” Journal of Pediatrics. 2014;164(2):223-225.Google Scholar
13. Botelho-Nevers, E, Gautret, P. Outbreaks associated to large open air festivals, including music festivals, 1980-2012. Eurosurveill. 2013;18(11):1-10.Google Scholar
14. Molloy, MS, Brady, F, Maleady, K. Impact of a single large mass gathering music event, from a series of such events, on a receiving hospital's emergency department (ED). Prehosp Disaster Med. 2013;28(1):S186.Google Scholar
15. Heiby, MJ, Barnhardt, W, Berry, T, Welcher, M, Brady, WJ. The impact of a mass gathering events with an on-site medical management team on municipal 911 emergency medical services. Am J Emerg Med. 2013;31(1):256-257.Google Scholar
16. Zielioski, A, Pawlak, BJ. Toolbox for implementation of surveillance at mass gatherings: surveillance during mass gatherings. 2013. http://www.rki.de/EN/Content/Prevention/React/Work/wp4/WP_4_ToolBox.pdf?__blob=publicationFile. Accessed March 16, 2014.Google Scholar
17. Arbon, P, Bridgewater, FHG, Smith, C. Mass gathering medicine: a predictive model for patient presentation and transport rates. Prehosp Disaster Med. 2001;16(3):150-158.Google Scholar