Lessons on Mass Gatherings Learned From the 2019 Union Cycliste Internationale Mountain Bike World Cup

Craven, P. D.; Hansroth, Joseph; Quedado, Kimberly; Goode, Christopher; Dragan, Shane; Monseau, Aaron J.; Balcik, Brenden J.; Chill, Nicholas; Findley, Scott

doi:10.7759/cureus.14275

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…For the 2019 event, 37.8 presentations were predicted with a total of 42 actual presentations, a 10% increase. 7 Characteristics of the presenting patients can be seen in Table 3 .…”

Section: Resultsmentioning

confidence: 99%

A Retrospective Application of the Arbon and Hartman Models to the Union Cycliste International Mountain Bike World Cup

Tucker,

Duncan,

Craven

et al. 2023

Prehosp. Disaster med.

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Introduction:Outdoor activities have accelerated in the past several years. The authors were tasked with providing medical care for the Union Cycliste International (UCI) mountain biking World Cup in Snowshoe, West Virginia (USA) in September 2021. The Hartman and Arbon models were designed to predict patient presentation and hospital transport rates as well as needed medical resources at urban mass-gathering events. However, there is a lack of standardized methods to predict injury, illness, and insult severity at rural mass gatherings.Study Objective:This study aimed to determine whether the Arbon model would predict, within 10%, the number of patient presentations to be expected and to determine if the event classification provided by the Hartman model would adequately predict resources needed during the event.Methods:Race data were collected from UCI event officials and injury data were collected from participants at time of presentation for medical care. Predicted presentation and transport rates were calculated using the Arbon model, which was then compared to the actual observed presentation rates. Furthermore, the event classification provided by the Hartman model was compared to the resources utilized during the event.Results:During the event, 34 patients presented for medical care and eight patients required some level of transport to a medical facility. The Arbon predictive model for the 2021 event yielded 30.3 expected patient presentations. There were 34 total patient presentations during the 2021 race, approximately 11% more than predicted. The Hartman model yielded a score of four. Based on this score, this race would be classified as an “intermediate” event, requiring multiple Advanced Life Support (ALS) and Basic Life Support (BLS) personnel and transport units.Conclusion:The Arbon model provided a predicted patient presentation rate within reasonable error to allow for effective pre-event planning and resource allocation with only a four patient presentation difference from the actual data. While the Arbon model under-predicted patient presentations, the Hartman model under-estimated resources needed due to the high-risk nature of downhill cycling. The events staffed required physician skills and air medical services to safely care for patients. Further evaluation of rural events will be needed to determine if there is a generalized need for physician presence at smaller events with inherently risky activities, or if this recurring cycling event is an outlier.

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“…For the 2019 event, 37.8 presentations were predicted with a total of 42 actual presentations, a 10% increase. 7 Characteristics of the presenting patients can be seen in Table 3 .…”

Section: Resultsmentioning

confidence: 99%

A Retrospective Application of the Arbon and Hartman Models to the Union Cycliste International Mountain Bike World Cup

Tucker,

Duncan,

Craven

et al. 2023

Prehosp. Disaster med.

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“…Sports operations staff, coaches/managers/equipment staff, and sports medicine and performance staff account for 26%, 35% and 24% of the entire staff delegation, respectively. Few studies comment on rates of illness, but do not offer investigation into reasoning behind the observed rates 14–19. However, it is likely that each of these groups have a greater density of face-to-face interactions simply by nature of their roles.…”

Section: Discussionmentioning

confidence: 99%

“…Few studies comment on rates of illness, but do not offer investigation into reasoning behind the observed rates. [14][15][16][17][18][19] However, it is likely that each of these groups have a greater density of face-to-face interactions simply by nature of their roles. These interactions thereby lead to inherent risk for developing an infection or dermatological illness, as these are commonly spread via contact or close proximity with others.…”

Section: Patterns Of Staff Member Illnessesmentioning

confidence: 99%

“…Epidemiological studies reporting illness and injury rates incurred by athletes at large-scale sporting competitions, such as the Olympic and Paralympic Games, have been extensively reported. [1][2][3][4][5][6][7][8][9][10][11][12][13] However, despite prior studies indicating that workforce staff make up a notable portion (5.1% to 61.8%) of those requiring medical care, [14][15][16][17][18][19] there is presently no research focusing on injuries and illnesses sustained by staff members from a single delegation.…”

Section: Introductionmentioning

confidence: 99%

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Incidence of staff injury and illness at the Tokyo 2020 and Beijing 2022 Olympic and Paralympic Games

Larson,

Hasley,

Post

et al. 2024

BMJ Open Sport Exerc Med

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ObjectiveTo report epidemiological data regarding injury and illness among the Team USA staff during the Tokyo 2020 Summer Olympic and Paralympic Games and Beijing 2022 Winter Olympic and Paralympic Games.MethodsA retrospective review of all Team USA staff (total staff, N=1703 (62.5% female); total staff days (SD)=34 489) medical encounters during the Tokyo 2020 Games and Beijing 2022 Games was conducted. Details related to injury and illness were evaluated. Incidence with 95% CI per 1000 staff days were calculated.ResultsA total of 32 illnesses (incidence [95% CI] 0.9 [0.6, 1.2]) and 23 injuries (incidence 0.7 [0.4, 0.9]) were sustained by the Team USA delegation staff members during the Tokyo 2020 Games and Beijing 2022 Games. Female staff reported more illnesses (illnesses proportion (IP) 2.9%; incidence 1.4 [0.8, 2.0]), while male staff incurred more injuries (IP 1.8%; incidence 0.9 [0.5, 1.3]). When stratified by physiological system, dermatological and infectious were the most common systems involved with illness (IP 0.5%; incidence 0.2 [0.1, 0.4]). Injuries to the upper limb were most common (IP 0.3%; incidence 0.3 [0.1, 0.5]).ConclusionInjury and illness rates among the Team USA staff during the Tokyo 2020 Games and Beijing 2022 Games were low, but notable. Knowledge of injury and illness risks contributes to staffing decisions and prevention strategies for staff supporting athletes during competition.

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Driving healthcare forward: The potential of mobile MRI and CT units in streamlining radiological services in Saudi Arabia - A narrative review

Hadi,

Hawsawi,

Abu Aqil

2024

Journal of Medical Imaging and Radiation Sciences

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Lessons on Mass Gatherings Learned From the 2019 Union Cycliste Internationale Mountain Bike World Cup

Cited by 3 publications

References 11 publications

A Retrospective Application of the Arbon and Hartman Models to the Union Cycliste International Mountain Bike World Cup

A Retrospective Application of the Arbon and Hartman Models to the Union Cycliste International Mountain Bike World Cup

Incidence of staff injury and illness at the Tokyo 2020 and Beijing 2022 Olympic and Paralympic Games

Driving healthcare forward: The potential of mobile MRI and CT units in streamlining radiological services in Saudi Arabia - A narrative review

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