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

@article{Lund2014MassgatheringHR,
  title={Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings},
  author={Adam Lund and Sheila A. Turris and Ron Bowles and Malinda Steenkamp and Alison Hutton and Jamie Ranse and Paul Arbon},
  journal={Prehospital and Disaster Medicine},
  year={2014},
  volume={29},
  pages={648 - 654}
}
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… 
Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings
TLDR
Consistent definitions of MG populations will support meta-analysis and pooling of data sources internationally, creating a foundation for risk assessment as well as illness and injury prediction modeling, and support methodology for evaluating health promotion, harm reduction, and clinical-response interventions at MGs.
Mass-gathering Health Research Foundational Theory: Part 2 - Event Modeling for Mass Gatherings
TLDR
The development of a series of event lenses that serve as a beginning “ MG event model,” complimenting the “MG population model” reported elsewhere are described, addressing a gap in the current body of knowledge.
Exploring International Views on Key Concepts for Mass-gathering Health through a Delphi Process
TLDR
This project explored the views and sought consensus of international MGH experts on previously published concepts around MGH to inform the development of a transnational minimum data set (MDS) with an accompanying data dictionary (DD).
Measuring the Masses: Understanding Health Outcomes Arising from Mass Gatherings, Reporting Gaps, and Recommendations (Paper 2)
TLDR
Coordinating post-event reporting through the consistent capture and publication of essential data points will allow researchers and clinicians to make comparisons between events and across event types with the goal of mitigating or obviating negative outcomes for individuals and communities.
Measuring the Masses: Mass-Gathering Medical Case Reporting, Conceptual Modeling – The DREAM Model (Paper 5)
TLDR
A layered model of essential conceptual components for post-event medical reporting is presented as the Data Reporting, Evaluation, & Analysis for Mass-Gathering Medicine (DREAM) model, providing an evolving conceptual model and laying the groundwork for exploring the relationships between categories of variables pertaining the health outcomes of MGs.
Measuring the Masses: Domains Driving Data Collection and Analysis for the Health Outcomes of Mass Gatherings (Paper 3)
TLDR
A set of domains for data that may support increasingly comprehensive, yet lean, reporting on the health outcomes of MGs are proposed, proposing a set of operationally relevant data domains that apply equally to small, medium, and large-sized events.
Improving Data Quality in Mass-Gatherings Health Research
TLDR
The authors propose underlying human, environmental, and logistical factors that may contribute to poor data quality at mass gatherings, and make specific recommendations for improvement through pre-event planning, on-site actions, and post-event follow-up.
Health Service Impact from Mass Gatherings: A Systematic Literature Review
TLDR
A recommendation for future mass-gathering research and evaluation is to link patient-level data from in-event mass gatherings to external health services, to more accurately inform future health planning for mass gatherings across the health care continuum.
Measuring the Masses: The Current State of Mass-Gathering Medical Case Reporting (Paper 1)
TLDR
Heterogeneity is a significant impediment to the functional use of published reports to further the science of MG planning and to improve health outcomes, and future work will aim to align and standardize reporting to improve the quality and value of event reporting.
Mass-gathering Health Research Foundational Theory: Part 1 - Population Models for Mass Gatherings—CORRIGENDUM
TLDR
This study highlights the need to understand more fully the role of social media in the planning and implementation of mass gatherings and the role that social media has in promoting awareness of these events.
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Consistent definitions of MG populations will support meta-analysis and pooling of data sources internationally, creating a foundation for risk assessment as well as illness and injury prediction modeling, and support methodology for evaluating health promotion, harm reduction, and clinical-response interventions at MGs.
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