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Ranse J. (2013). Injury patterns and crowd behaviour at mass gathering events. Sex, Drugs, and Rock and Roll - St John Ambulance Australia (ACT), Canberra, ACT, 14th September.
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INJURY PATTERNS AND CROWD BEHAVIOUR AT MASS GATHERING EVENTS
Jamie RanseAssistant Professor
University of Canberra
www.jamieranse.com
twitter.com/jamieranse
youtube.com/jamieranse
linkedin.com/in/jamieranse
• Definition
• Conceptual model
• Workload characteristics
• Workload prediction
• Event design
• Event managers
• Case study
overview
definition
Class Subclass Persons Resources Example
Mass gathering
Small 200 – 1,500 Local area Local fair
Medium 1,500 – 10,000 Local area Local sports game
Large 10,000 – 100,000 Local +/- State Concert
Major mass gathering 100,000 – 250,000 State +/- Interstate Music festivalAgricultural show
Super mass gathering 250,000 – 500,000 State and Interstate Motor sports event
Extreme mass gathering
500,000 – 1,000,00National +/- international
Religious festival
Mega mass gathering 1,000,000+National and International
Olympics
conceptual model
workload characteristics
• Other extreme events
• Can we predict workload?
temperature
bounded or not
ETOH / drug availability
humidity
participant numbers
day / nightindoors / outdoors
crowd behaviour
• What factors influence workload / presentations?
level of onsite care
age of participants
duration
geography
workload characteristics and conceptual model
workload prediction
• Why predict workload?• What to predict?
– Patient presentation rate (PPR)
0.14 to 90/1,000 (majority 0.5 and 2.6/1,000)– Transport to hospital rate (TTHR)
0.01 to 0.55/1,000– Referral to hospital rate
5% - 10% of PPR
• How?– Predictive models– Historical prediction
event design
• Crowd behaviour– Music festivals
– Spaces
• Patient access
event managers
• Health service– What level of service do you need?
– Health risk assessment
• Event managers– Overall risk management
– Patient information: confidentiality v duty of care
event managers
implications
• Pre-ambulance (PPR)
• Pre-hospital (TTHR)
implications
• Pre-ambulance (PPR)
• Pre-hospital (TTHR)
• Emergency Department
(RTHR)
implications
• Pre-ambulance
• Pre-hospital
• Emergency Department
• Hospital– surgery
case study
To understand the characteristics of people who present as patients to on-site health care at outdoor music festivals in Australia
aim
• Retrospective review of patient report forms • 26 outdoor music festivals • Four different states of Australia• Minimum data set
– Illness– Injury – Environmental– Mental Health
design and setting
• 4950 presentations
• Almost two thirds were female (n=3087, 62.4%)
• The mean age of all patient presentations was 21.3 (5.8) years
• The majority of patients (n=3875, 78.3%) were ≤25 years of age
demographics
• The majority of patient presentations (n=2766, 55.9%) presented with illness related concerns
• The risk of illness was 1.7 times (OR=1.71; 95% CI 1.51-1.94; p<0.001) higher for females than males in the ≤25 year age group
• Most common presenting problem was headache (n=1389, 52.9%).
• Pain (n=264 10%), asthma (n=216 8.2%), and nausea and vomiting (n=211 8%)
illness
• The risk of a female sustaining an injury was almost half (OR=0.54; 95% CI 0.47-0.62; p<0.001) that of males
• The main types of injury presentations were superficial lacerations (n=281; 20.4%); sprain or strains (n=268; 19.2%), and head injuries (concussion) (n=168; 11.9%)
• Crushing injuries; blisters and foreign bodies; external to eye was significantly higher for females than males
injury
• Alcohol related presentations most common (n=250 32.8%)
• Substance related (n=135 17.7%), • Combined alcohol and substance use (n=125 16.4%)• Heat exhaustion more prevalent for females (p=<0.001),
while substance related presentations more prevalent for males (p=<0.001)
environment
• Gender didn’t demonstrate a significant risk for mental health related presentations
• 29 cases overall: average of one per event
mental health
• Most patients returned to the event
• Environmental-related category highest TTHR
outcome
INJURY PATTERNS AND CROWD BEHAVIOUR AT MASS GATHERING EVENTS
Jamie RanseAssistant Professor
University of Canberra
www.jamieranse.com
twitter.com/jamieranse
youtube.com/jamieranse
linkedin.com/in/jamieranse