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Mass gatherings are common in Australia. The interplay of variables, including crowd density and behavior, weather, and the consumption of alcohol and other drugs, can pose a unique set of challenges to attendees’ well-being. On-site health services are available at most mass gatherings and reduce the strain on community health facilities. In order to efficiently plan and manage these services, it is important to be able to predict the number and type of presenting problems at mass gatherings.
Problem
There is a lack of reliable tools to predict patient presentations at mass gatherings. While a number of factors have been identified as having an influence on attendees’ health, the exact contribution of these variables to patient load is poorly understood. Furthermore, predicting patient load at mass gatherings is an inherently nonlinear problem, due to the nonlinear relationships previously observed between patient presentations and many event characteristics.
Methods
Data were collected at 216 Australian mass gatherings and included event type, crowd demographics, and weather. Nonlinear models were constructed using regression trees. The full data set was used to construct each model and the model was then used to predict the response variable for each event. Nine-fold cross validation was used to estimate the error that may be expected when applying the model in practice.
Results
The mean training errors for total patient presentations were very high; however, the distribution of errors per event was highly skewed, with small errors for the majority of events and a few large errors for a small number of events with a high number of presentations. The error was five or less for 40% of events and 15 or less for 85% of events. The median error was 6.9 presentations per event.
Conclusion:
This study built on previous research by undertaking nonlinear modeling, which provides a more realistic representation of the interactions between event variables. The developed models were less useful for predicting patient presentation numbers for very large events; however, they were generally useful for more typical, smaller scale community events. Further research is required to confirm this conclusion and develop models suitable for very large international events.
Arbon P, Bottema M, Zeitz K, Lund A, Turris S, Anikeeva O, Steenkamp M. Nonlinear modelling for predicting patient presentation rates for mass gatherings. Prehosp Disaster Med. 2018;33(4):362–367
Mass gatherings are complex events that present a unique set of challenges to attendees’ health and well-being. There are numerous factors that influence the number and type of injuries and illnesses that occur at these events, including weather, event and venue type, and crowd demographics and behavior.
Problem
While the impact of some factors, such as weather conditions and the availability of alcohol, on patient presentations at mass gatherings have been described previously, the influence of many other variables, including crowd demographics, crowd behavior, and event type, is poorly understood. Furthermore, a large number of studies reporting on the influence of these variables on patient presentations are based on anecdotal evidence at a single mass-gathering event.
Methods
Data were collected by trained fieldworkers at 15 mass gatherings in South Australia and included event characteristics, crowd demographics, and weather. De-identified patient records were obtained from on-site health care providers. Data analysis included the calculation of patient proportions in each variable category, as well as the total number of patient presentations per event and the patient presentation rate (PPR).
Results
The total number of expected attendees at the 15 mass gatherings was 303,500, of which 146 presented to on-site health care services. The majority of patient presentations occurred at events with a mean temperature between 20°C and 25°C. The PPR was more than double at events with a predominantly male crowd compared to events with a more equal sex distribution. Almost 90.0% of patient presentations occurred at events where alcohol was available.
Conclusion:
The results of the study suggest that several weather, crowd, and event variables influence the type and number of patient presentations observed at mass-gathering events. Given that the study sample size did not allow for these interactions to be quantified, further research is warranted to investigate the relationships between alcohol availability, crowd demographics, crowd mobility, venue design, and injuries and illnesses.
Anikeeva O, Arbon P, Zeitz K, Bottema M, Lund A, Turris S, Steenkamp M. Patient presentation trends at 15 mass-gathering events in South Australia. Prehosp Disaster Med. 2018;33(4):368–374.
The management of mass gatherings encompasses a wide range of activities because of varying types of events and baseline medical and health infrastructures. A classification system for mass gatherings can aid in the planning process internationally and also achieve a commonality of language for describing future events. This cycle of event, analysis, training, planning, and new event should be the goal for those involved in organizing mass gathering medical care. The event plan specifies the various training requirements, certifications, and indemnity/malpractice or insurance required of the medical director and deputy. Management of a mass gathering from the medical perspective requires human resources, medical equipment, pharmaceuticals, and medical facilities with sufficient examination rooms on site. As mass gatherings become more frequent, more experts need to be trained and more research performed to ensure continued reductions in morbidity and mortality among those attending or managing such events.
Emergency medical services (EMS) responses to
mass gatherings have been described frequently,
but there are few reports describing the response
to a single-day gathering of large magnitude.
Objective:
This report describes the EMS response to the
largest single-day, ticketed concert held in North
America: the 2003 “Toronto Rocks!” Rolling Stones
Concert.
Methods:
Medical care was provided by paramedics,
physicians, and nurses. Care sites included
ambulances, medically equipped, all-terrain
vehicles, bicycle paramedic units, first-aid
tents, and a 124-bed medical facility that
included a field hospital and a rehydration unit.
Records from the first-aid tents, ambulances,
paramedic teams, and rehydration unit were
obtained. Data abstracted included patient
demographics, chief complaint, time of incident,
treatment, and disposition.
Results:
More than 450,000 people attended the concert and
1,870 sought medical care (42/10,000 attendees).
No record was kept for the 665 attendees simply
requesting water, sunscreen, or bandages. Of the
remaining 1,205 patients, the average of the ages
was 28 ±11 years, and 61% were female.
Seven-hundred, ninety-five patients (66%) were
cared for at one of the first-aid tents.
Physicians at the tents assisted in patient
management and disposition when crowds restricted
ambulance movement. Common complaints included
headache (321 patients; 27%), heat-related
complaints (148; 12%), nausea or vomiting (91;
7.6%), musculoskeletal complaints (83; 6.9%), and
breathing problems (79; 6.6%). Peak activity
occurred between 14:00 and 19:00 hours, when 102
patients per hour sought medical attention.
Twenty-four patients (0.5/10,000) were transferred
to off-site hospitals.
Conclusions:
This report on the EMS response, outcomes, and
role of the physicians at a large single-day mass
gathering may assist EMS planners at future
events.
Mass-gatherings events provide a difficult setting for which to plan an appropriate emergency medical response. Many of the variables that affect the level and types of medical needs, have not been fully researched. This review examines these variables.
Methods:
An extensive review was conducted using the computerized databases Medline and Healthstar from 1977 through May 2002. Articles selected contained information pertaining to mass-gathering variables. These articles were read, abstracted, analyzed, and compiled.
Results:
Multiple variables are present during a mass gathering, and they interact in complex and dynamic ways. The interaction of these variables contributes to the number of patients treated at an event (medical usage rate) as well as the observed injury patterns. Important variables include weather, event type, event duration, age, crowd mood and density, attendance, and alcohol and drug use.
Conclusions:
Developing an understanding of the variables associated with mass gatherings should be the first step for event planners. After these variables are considered, a thorough needs analysis can be performed and resource allocation can be based on objective data.