Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings. Issue 6 (17th November 2014)
- Record Type:
- Journal Article
- Title:
- Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings. Issue 6 (17th November 2014)
- Main Title:
- Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings
- Authors:
- Lund, Adam
Turris, Sheila A.
Bowles, Ron
Steenkamp, Malinda
Hutton, Alison
Ranse, Jamie
Arbon, Paul - Abstract:
- <abstract abstract-type="normal"> <title>Abstract</title> <sec id="abs1" sec-type="general"> <title>Background</title> <p>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.</p> </sec> <sec id="abs2" sec-type="general"> <title>Process</title> <p>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.</p> </sec> <sec id="abs3" sec-type="general"> <title>Findings and Interpretation</title> <p>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<abstract abstract-type="normal"> <title>Abstract</title> <sec id="abs1" sec-type="general"> <title>Background</title> <p>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.</p> </sec> <sec id="abs2" sec-type="general"> <title>Process</title> <p>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.</p> </sec> <sec id="abs3" sec-type="general"> <title>Findings and Interpretation</title> <p>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.</p> <p>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.</p> </sec> <sec id="abs4" sec-type="conclusion"> <title>Conclusions</title> <p>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.</p> <p> <mixed-citation id="ref" publication-type="journal"> <string-name> <given-names>A</given-names> <x content-type="archive" xml:space="preserve"> </x> <surname>Lund</surname> </string-name>, <string-name><given-names>SA</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Turris</surname></string-name>, <string-name><given-names>R</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Bowles</surname></string-name>, <string-name><given-names>M</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Steenkamp</surname></string-name>, <string-name><given-names>A</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Hutton</surname></string-name>, <string-name><given-names>J</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Ranse</surname></string-name>, <string-name><given-names>P</given-names><x content-type="archive" xml:space="preserve"> </x><surname>Arbon</surname></string-name>. <article-title>Mass-gathering health research foundational theory: part 1 - population models for mass gatherings</article-title>. <source>Prehosp Disaster Med</source>. <year>2014</year>;<volume>29</volume>(<issue>6</issue>):<fpage>1</fpage>-<lpage>7</lpage></mixed-citation>.</p> </sec> </abstract> … (more)
- Is Part Of:
- Prehospital and disaster medicine. Volume 29:Issue 6(2014)
- Journal:
- Prehospital and disaster medicine
- Issue:
- Volume 29:Issue 6(2014)
- Issue Display:
- Volume 29, Issue 6 (2014)
- Year:
- 2014
- Volume:
- 29
- Issue:
- 6
- Issue Sort Value:
- 2014-0029-0006-0000
- Page Start:
- 648
- Page End:
- 654
- Publication Date:
- 2014-11-17
- Subjects:
- Emergency medical services -- Periodicals
Emergency medicine -- Periodicals
Disaster medicine -- Periodicals
616.025 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=PDM ↗
- DOI:
- 10.1017/S1049023X14001216 ↗
- Languages:
- English
- ISSNs:
- 1049-023X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 3173.xml