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.

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.

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.

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.

Current knowledge about mass-gathering health (MGH) fails to adequately inform the understanding of mass gatherings (MGs) because of a relative lack of theory development and adequate conceptual analysis. This report describes the development of a series of event lenses that serve as a beginning “MG event model,” complimenting the “MG population model” reported elsewhere.

Existing descriptions of “MGs” were considered. Analyzing gaps in current knowledge, the authors sought to delineate the population of events being reported. Employing a consensus approach, the authors strove to capture the diversity, range, and scope of MG events, identifying common variables that might assist researchers in determining when events are similar and might be compared. Through face-to-face group meetings, structured breakout sessions, asynchronous collaboration, and virtual international meetings, a conceptual approach to classifying and describing events evolved in an iterative fashion.

Embedded within existing literature are a variety of approaches to event classification and description. Arising from these approaches, the authors discuss the interplay between event demographics, event dynamics, and event design. Specifically, the report details current understandings about event types, geography, scale, temporality, crowd dynamics, medical support, protective factors, and special hazards. A series of tables are presented to model the different analytic lenses that might be employed in understanding the context of MG events.

The development of an event model addresses a gap in the current body of knowledge vis a vis understanding and reporting the full scope of the health effects related to MGs. Consistent use of a consensus-based event model will support more rigorous data collection. This in turn will support meta-analysis, create a foundation for risk assessment, allow for the pooling of data for illness and injury prediction, and support methodology for evaluating health promotion, harm reduction, and clinical response interventions at MGs.

TurrisSA , LundA , HuttonA , BowlesR , EllersonE , SteenkampM , RanseJ , ArbonP . Mass-gathering Health Research Foundational Theory: Part 2 - Event Modeling for Mass Gatherings. Prehosp Disaster Med. 2014;29(6):1-9.