Mass gatherings are events where many people come together at a specific location for a specific purpose, such as concerts, sports events, or religious gatherings, within a certain period of time. In mass-gathering studies, many rates and ratios are used to assess the demand for medical resources. Understanding such metrics is crucial for effective planning and intervention efforts. Therefore, this systematic review aims to investigate the usage of rates and ratios reported in mass-gathering studies.

In this systematic review, the PRISMA guidelines were followed. Articles published through December 2023 were searched on Web of Science, Scopus, Cochrane, and PubMed using the specified keywords. Subsequently, articles were screened based on titles, abstracts, and full texts to determine their eligibility for inclusion in the study. Finally, the articles that were related to the study’s aim were evaluated.

Out of 745 articles screened, 55 were deemed relevant for inclusion in the study. These included 45 original research articles, three special reports, three case presentations, two brief reports, one short paper, and one field report. A total of 15 metrics were identified, which were subsequently classified into three categories: assessment of population density, assessment of in-event health services, and assessment of out-of-event health services.

The findings of this study revealed notable inconsistencies in the reporting of rates and ratios in mass-gathering studies. To address these inconsistencies and to standardize the information reported in mass-gathering studies, a Metrics and Essential Ratios for Gathering Events (MERGE) table was proposed. Future research should promote consistency in terminology and adopt standardized methods for presenting rates and ratios. This would not only enhance comparability but would also contribute to a more nuanced understanding of the dynamics associated with mass gatherings.

To describe the health-care resources implemented during the Italian Formula 1 Grand Prix (F1GP) and to calculate the patient presentation rate (PPR) based on both real data and a prediction model.

Observational and descriptive study conducted from September 9 to September 11, 2022, during the Italian F1GP hosted in Monza (Italy). Maurer’s formula was applied to decide the number and type of health resources to be allocated. Patient presentation rate (PPR) was computed based on real data (PPR_real) and based on the Arbon formula (PPR_est).

Of 336,000 attendees, n = 263 requested medical assistance with most of them receiving treatment at the advanced medical post, and n = 16 needing transport to the hospital. The PPR_real was 51 for Friday, 78 for Saturday, 134 for Sunday, and 263 when considering the whole event as a single event. The PPR_est resulted in 85 for Friday, 93 for Saturday, 97 for Sunday, and 221 for the total population.

A careful organization of health-care resources could mitigate the impact of the Italian F1GP on local hospital facilities. The Arbon formula is an acceptable model to predict and estimate the number of patients requesting medical assistance, but further investigation needs to be conducted to implement the model and tailor it to broader categories of MGE.

To validate the Belgian Plan Risk Manifestations (PRIMA) model, actual patient presentation rates (PPRs) from Belgium’s largest football stadium were compared with predictions provided by existing models and the Belgian PRIMA model.

Actual patient presentations gathered from 41 football games (2010-2019) played at the King Baudouin Stadium (Brussels, Belgium) were compared with predictions by existing models and the PRIMA model. All attendees who sought medical help from in-event health services (IEHS) in the stadium or called 1-1-2 within the closed perimeter around the stadium were included. Data were analyzed by ANOVA, Pearson correlation tests, and Wilcoxon singed-rank test.

A total of 1,630,549 people attended the matches, with 626 people needing first aid. Both the PRIMA and the Hartman model over-estimated the number of patient encounters for each occasion. The Arbon model under-estimated patient encounters for 9.75% (95% CI, 0.49-19.01) of the events. When comparing deviations in predictions between the PRIMA model to the other models, there was a significant difference in the mean deviation (Arbon: Z = −5.566, P <.001, r = −.61; Hartman: Z = −4.245, P <.001, r = .47).

When comparing the predicted patient encounters, only the Arbon model under-predicted patient presentations, but the Hartman and the PRIMA models consistently over-predicted. Because of continuous over-prediction, the PRIMA model showed significant differences in mean deviation of predicted PPR. The results of this study suggest that the PRIMA model can be used during planning for domestic and international football matches played at the King Baudouin Stadium, but more data and further research are needed.

Case reports are commonly used to report the health outcomes of mass gatherings (MGs), and many published reports of MGs demonstrate substantial heterogeneity of included descriptors. As such, it is challenging to perform rigorous comparisons of health services and outcomes between similar and dissimilar events. The degree of variation in published reports has not yet been investigated.

Examine patterns of post-event medical reporting in the existing literature and identify inconsistencies in reporting.

A systematic review of case reports was conducted. Included were English studies, published between January 2009 and December 2018, in Prehospital and Disaster Medicine (PDM) or Current Sports Medicine Reports (CSMR). Analysis of each paper was used to develop a list of 27 categories of data.

Seventy-five studies were initially reviewed with 54 publications meeting the inclusion criteria. Forty-two were full case reports (78%) and 12 were conference proceedings (22%). Of the 27 categories of data studied, only 13 were consistently reported in more than 50% of publications. Reporting patterns included inconsistent use of terminology/language and variable retrievability of reports. Reporting on event descriptors, hazard and risk analysis, and clinical outcomes were also inconsistent.

Case reports are essential tools for researchers and event team members such as medical directors and event producers. The authors found that current case reports, in addition to being inconsistent in content, were generally descriptive rather than explanatory; that is, focused on describing the outcomes as opposed to exploring possible connections between context and health outcomes.

This paper quantifies and demonstrates the current state of heterogeneity in MG event reporting. This heterogeneity is a significant impediment to the functional use of published reports to further the science of MG planning and to improve health outcomes. Future work based on the insights gained from this analysis will aim to align and standardize reporting to improve the quality and value of event reporting.

Shopping centers (SCs) are social areas with a group of commercial establishments which attract customers of numerous people every day. However, analysis of urgent health conditions and provided health care in SCs has not been performed so far.

The aim of the study was to perform a comparative analysis of clients visiting SCs and demographics, complaints, and health care of patients admitted to Emergency Medical Intervention Units (EMIU) located in grand SCs in Ankara, Turkey.

Customer and health care records of nine grand SCs in Ankara from January 1, 2018 through December 31, 2018 were evaluated retrospectively. Health care services in EMIUs of SCs were provided by employed medical staff. Data including demographic characteristics, complaints, treatment protocols, discharge, and referral to hospital of the patients were retrospectively analyzed from medical registration forms.

Medical records of nine grand SCs were analyzed. Number of customers could not be obtained in three SCs due to privacy issues and were not included in patient presentation rate (PPR) and transport-to-hospital rate (TTHR) calculation. Total number of customers in the remaining six SCs were 53,277,239. The total number of patients seeking medical care was 6,749. The number of patients seeking health care in six SCs with known number of customers was 4,498 and PPR ranged from 0.018 to 0.381 patients per 1,000 attendants. The median age of the recorded 4,065 patients (60.2%) was 28 (interquartile range [IQR]: 38-21), and 3,611 (53.5%) of the patients admitted to EMIUs were female. The number of patients treated in the SC was 4,634 (68.6%) and 189 patients (2.8%) were transferred-to-hospital by ambulance for further evaluation and treatment. Transportation to hospital was required in 125 patients who sought medical care in six SCs which provided total number of customers, and TTHR ranged from 0.000 to 0.005 patients per 1,000 attendants. No sudden cardiac death was seen. Medical conditions were the primary reasons for seeking health care. The most frequent causes of presentation were laceration and abrasions (639 patients, 9.4%).

The PPR and TTHR in SCs are low. The most common causes of presentation are minor conditions and injuries. Majority of urgent medical conditions in SCs can be managed by health care providers in EMIUs.

A Belgian predictive medical resource tool, Plan Risk Manifestations (PRIMA), for the prediction of the number of patient encounters at mass gatherings (MGs) has recently been developed, in addition to the existing models of Arbon and Hartman. This study presents the results of the validation process for the PRIMA model for music MGs.

A retrospective study was conducted using data gathered from music MGs in the province of Antwerp (Belgium) during the period of 2012-2016. Data from 87 music MGs were used for the study. The forecast of medical resources for these events was determined by entering the characteristics of individual events into the Arbon, Hartman, and PRIMA models. In order to determine if the PRIMA model is under- or over-predictive, the data gathered were retrospectively compared to the predicted number of resources needed using the aforementioned models. Statistical analysis included means, medians, and interquartile ranges (IQRs). Nonparametric related samples test (Wilcoxon Samples Signed Rank Test) for comparison of the median in deviations in predictions of patient presentation rates (PPRs) was performed using SPSS version 23 (IBM Corp.; Armonk, New York USA). Confidence interval levels were set at 95% and results were deemed statistically significant at P <.05. This triple comparison was used to determine the overall performance of all three models.

All three models had an acceptable rate of over-prediction of number of patient encounters ([Arbon 25.29%; 95% CI, 30.91-43.74]; [Hartman 29.89%; 95% CI, 57.10-68.90]; and [PRIMA 19.54%; 95% CI, 57.80-76.20]). But all models also had a high rate of under-prediction of number of patient encounters ([Arbon 74.71%; 95% CI, 453.31-752.52]; [Hartman 70.11%; 95% CI, 546.90-873.77]; and [PRIMA 78.16%; 95% CI, 288.91-464.89]). Only the PRIMA model succeeded in the correct prediction of the number of patient encounters on two occasions (2.3%).

Results of this study are in-line with existing literature. When comparing the predicted patient encounters, all three models had high rates of under-prediction and moderate rates of over-prediction. When comparing mean deviations, the PRIMA model had the lowest mean deviation of all predicted PPRs. Belgian events of the types included in the presented data may use the PRIMA model with confidence to predict PPRs and estimate the in-event health services (IEHS) requirements.

Mass gatherings (MGs) grow in frequency around the world. With the intrinsic potential for significant health risks for all involved, MGs pose a challenge for those responsible for the provision of on-site medical care. Belgian law obliges local governments to identify and analyze the risks involving a MG. Though medical risk factors are long known, all too often, resourcing for in-event health services is based on anecdotal and previous experiences.

Despite the fast-evolving science on MGs, the lack of reliable tools – based on empirical and analytical approaches – to predict patient presentation rates (PPRs) at MGs remains.

A two-step method was followed to develop, update, and support a Plan Risk Manifestation (PRIMA) program. First, a continuous systematic literature review was conducted. Once developed, the model was run using data obtained from Belgian Federal Public Service (FPS; Brussels, Belgium) Health, Food Chain Safety, and Environment (HFCSE); event organizers; and municipalities.

In total, 231 studies and documents were included to form the program. With the data provided, three variables were computed to run the calculation model to predict the PPR. Three medical risk axes were defined for this model: (1) isolation risk; (2) population risk; and (3) risk at illness. A combined dataset was derived from the prediction of the PRIMA program combined with the actual data obtained after the MG. This proved a solid basis for the calculation model of the PRIMA program.

Despite that validation is needed, the PRIMA program and its prediction model for PPRs at MGs carries the promise of a general, applicable prediction and risk analysis tool for a multitude of events.

This review discusses the need for consistency in mass-gathering research and evaluation from a psychosocial perspective.

Mass gatherings occur frequently throughout the world. Having an understanding of the complexities of mass gatherings is important to determine required health resources. Factors within the environmental, psychosocial, and biomedical domains influence the usage of health services at mass gatherings. A standardized approach to data collection is important to identify a consistent reporting standard for the psychosocial domain.

This research used an integrative literature review design. Manuscripts were collected using keyword searches from databases and journal content pages from 2003 through 2018. Data were analyzed and categorized using the existing minimum data set as a framework.

In total, 31 manuscripts met the inclusion criteria. The main variables identified were use of alcohol or drugs, crowd behavior, crowd mood, rationale, and length of stay.

Upon interrogating the literature, the authors have determined that the variables fall under the categories of alcohol or drugs; maladaptive and adaptive behaviors; crowd behavior, crowd culture, and crowd mood; reason for attending event (motivation); duration; and crowd demographics. In collecting psychosocial data from mass gatherings, an agreed-upon set of variables that can be used to collect de-identified psychosocial variables for the purpose of making comparisons across societies for mass-gathering events (MGEs) would be invaluable to researchers and event clinicians.

This paper discusses the need for consistency in mass-gathering research and evaluation from an environmental reporting perspective.

Mass gatherings occur frequently throughout the world. Having an understanding of the complexities of mass gatherings is important to inform health services about the possible required health resources. Factors within the environmental, psychosocial, and biomedical domains influence the usage of health services at mass gatherings. A minimum data set (MDS) has been proposed to standardize collection of biomedical data across various mass gatherings, and there is a need for an environmental component. The environmental domain includes factors such as the nature of the event, availability of drugs or alcohol, venue characteristics, and meteorological factors.

This research used an integrative literature review design. Manuscripts were collected using keyword searches from databases and journal content pages from 2003 through 2018. Data were analyzed and categorized using the existing MDS as a framework.

In total, 39 manuscripts were identified that met the inclusion criteria.

In collecting environmental data from mass gatherings, there must be an agreed-upon MDS. A set of variables can be used to collect de-identified environmental variables for the purpose of making comparisons across societies for mass-gathering events (MGEs).

Large-scale mass-sporting events are increasingly requiring greater prehospital event planning and preparation to address inherent event-associated medical conditions in addition to incidents that may be unexpected. The Bank of America Chicago Marathon (Chicago, Illinois USA) is one of the largest marathons in the world, and with the improvement of technology, the use of historical patient and event data, in conjunction with environmental conditions, can provide organizers and public safety officials a way to plan based on injury patterns and patient demands for care by predicting the placement and timing of needed medical support and resources.

During large-scale events, disaster planning and preparedness between event organizers, Emergency Medical Services (EMS), and local, state, and federal agencies is critical to ensure participant and public safety.

This study looked at the Bank of America Chicago Marathon, a significant endurance event, and took a unique approach of reviewing digital runner data retrospectively over a five-year period to establish patterns of medical demand geographically, temporally, and by the presenting diagnoses. Most medical complaints were musculoskeletal in nature; however, there were life-threatening conditions such as hyperthermia and cardiac incidents that highlight the need for detailed planning, coordination, and communication to ensure a safe and secure event.

The Chicago Marathon is one of the largest marathons in the world, and this study identified an equal number of participants requiring care on-course and at the finish line. Most medical complaints were musculoskeletal in nature; however, there were life-threatening conditions such as hyperthermia and cardiac incidents that highlight the need for detailed planning, multi-disciplined coordination, and communication to ensure a safe and secure event. As technology has evolved, the use, analysis, and implementation of historical digital data with various environmental conditions can provide organizers and public safety officials a map to plan injury patterns and patient demands by predicting the placement and timing of needed medical support, personnel, and resources.

Music festivals are globally attended events that bring together performers and fans for a defined period of time. These festivals often have on-site medical care to help reduce the impact on local health care systems. Historically, the literature suggests that patient transfers off-site are frequently related to complications of substance use. However, there is a gap in understanding why patients are transferred to hospital when an on-site medical team, capable of providing first aid services blended with a higher level of care (HLC) team, is present.

The purpose of this study is to better understand patterns of injuries and illnesses that necessitate transfer when physician-led HLC teams are accessible on-site.

This is a prospective, descriptive case series analyzing patient encounter documentation from four large-scale, North American, multi-day music festivals.

On-site medical teams that included HLC team members were present for the duration of each festival, so every team was able to “treat and release” when clinically appropriate. Over the course of the combined 34 event days, there were 10,406 patient encounters resulting in 156 individuals being transferred off-site for assessment, diagnostic testing, and/or treatment. A minority of patients seen were transferred off-site (1.5%). The patient presentation rate (PPR) was 16.5/1,000. The ambulance transfer rate (ATR) was 0.12/1,000 attendees, whereas the total transfer-to-hospital rate (TTHR), when factoring in non-ambulance transport, was 0.25/1,000. In contrast to existing literature on transfers from music festivals, the most common reason for transfer off-site was for musculo-skeletal (MSK) injuries (53.8%) that required imaging.

The presence of on-site HLC teams impacted the case mix of patients transferred to hospital, and may reduce the number of transfers for intoxication. Confounding preconceptions, patients in the present study were transferred largely for injuries that required specialized imaging and testing that could not be performed in an out-of-hospital setting. These results suggest that a better understanding of the specific effects on-site HLC teams have on avoiding off-site transfers will aid in improving planning for music festivals. The findings also identify areas for further improvement in on-site care, such as integrated on-site radiology, which could potentially further reduce the impact of music festivals on local health services. The role of non-emergency transport vehicles (NETVs) deserves further attention.

TurrisSA, CallaghanCW, RabbH, MunnMB, LundA. On the Way Out: An Analysis of Patient Transfers from Four Large-Scale North American Music Festivals Over Two YearsPrehosp Disaster Med. 2019;34(1):72–81.

There is insufficient research on medical care at mass-gathering events (MGEs) on college and university campuses. Fun Day is an annual celebratory day held at Skidmore College (Saratoga Springs, New York USA), a small liberal arts college in the Northeastern United States. Fun Day is focused around an outdoor music festival; students also congregate and celebrate throughout the surrounding campus. To improve care and alleviate strain on local resources, a model was developed for the provision of emergency care by a collegiate-based, volunteer first-response service – Skidmore College Emergency Medical Services (EMS) – in coordination with a contracted, private ambulance service.

The aims of this study were to: (1) analyze medical usage rates and case mixes at Fun Day over a four-year period, and to (2) describe the collegiate-based first response model for MGEs.

Data were collected retrospectively from event staff, college administrators, and Skidmore College EMS on event-related variables, patient encounters, and medical operations at Fun Day over a four-year period (2014-2017).

Annual attendance at the music festival was estimated at 2,000 individuals. Over four years, 54 patients received emergency medical care on campus on Fun Day, and 18 (33.3%) were transported to the emergency department. On-site contracted ambulances transported 77.8% of patients who were transported to the emergency department; mutual aid was requested for the other 22.2% of transports. The mean (SD) patient presentation rate (PPR) was 7.0 (SD = 1.0) per 1,000 attendees. The mean (SD) transport-to-hospital rate (TTHR) was 2.0 (SD = 1.0) per 1,000 attendees. Thirty (55.6%) patients presented with intoxication, seven (13.0%) with laceration(s), and five (9.3%) with head trauma as the primary concern. Medical command was established by volunteer undergraduate students. Up to 16 volunteer student first responders (including emergency medical technicians [EMTs]) were stationed on campus, in addition to two contracted ambulances at the Basic Life Support (BLS) and Advanced Life Support (ALS) levels. Operational strategies included: mobile first response crews, redundant communication systems, preventative education, and harm reduction.

High medical usage rates were observed, primarily due to alcohol/illicit substance use and traumatic injuries. The provision of emergency care by a collegiate-based first response service in coordination with a contracted, private ambulance agency serves as an innovative model for mass-gathering medical care on college and university campuses.

FriedmanNMG, O’ConnorEK, MunroT, GoroffD.Mass-Gathering Medical Care Provided by a Collegiate-Based First Response Service at an Annual College Music Festival and Campus-Wide Celebration. Prehosp Disaster Med. 2019;34(1):98–103.

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.

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.

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.

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.

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.

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.

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).

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.

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.

Mass crowds outside the routine population create a burden of disease on Emergency Medical Services (EMS). The need for EMS in various mass-crowd events may vary. It is especially important to determine the EMS requirement that emerges during the historic commemoration ceremonies in Çanakkale (Turkey).

This study aims to determine the unique challenges in the planning of EMS responses provided for people from various countries at the commemoration ceremony for a 100-year-old war and to identify the medical provision of those services.

This descriptive study examined the patient applications in the Çanakkale EMS at the commemoration ceremonies for the 100th anniversary of Gallipoli Wars (Çanakkale Amphibious Wars – Turkey) on April 24-25, 2015.

A total of 221 cases were handled by 112 EMS in the ceremony area. Of those, 87.3% of the cases applied to a mobile operating room (MOR) stationed in the ceremony area while 12.7% of them applied directly to the health care team in a large area in the ceremony area. Overall, 13.1% of the cases were transferred to the hospital for further evaluation and treatment. Patient presentation rate (PPR) of the patients who were treated during the two days was 4.42, and transfer to hospital rate (TTHR) of the cases transferred to the hospital was calculated to be 0.58.

Further studies may create models in regard to the estimations on mass and needs based on the data of previous organizations.

KoçakH, ÇalışkanC, SönmezlerMS, EliuzK, KüçükdurmazF. Analysis of Medical Responses in Mass Gatherings: The Commemoration Ceremonies for the 100th Anniversary of the Battle of Gallipoli. Prehosp Disaster Med. 2018;33(3):288–292.

Moshing is a violent form of dancing found world-wide at rock concerts, festivals, and electronic dance music events. It involves crowd surfing, shoving, and moving in a circular rotation. Moshing is a source of increased morbidity and mortality. The goal of this study was to report epidemiologic information on patient presentation rate (PPR), transport to hospital rate (TTHR), and injury patterns from patients who participated in mosh-pits.

Subjects were patrons from mosh-pits seeking medical care at a single venue. The events reviewed were two national concert tours which visited this venue during their tour. The eight distinct events studied occurred between 2011 and 2014. Data were collected retrospectively from prehospital patient care reports (PCRs). A single Emergency Medical Service (EMS) provided medical care at this venue. The following information was gathered from each PCR: type of injury, location of injury, treatment received, alcohol or drug use, Advanced Life Support/ALS interventions required, age and gender, disposition, minor or parent issues, as well as type of activity engaged in when injured.

Attendance for the eight events ranged from 5,100 to 16,000. Total patient presentations ranged from 50 to 206 per event. Patient presentations per ten thousand (PPTT) ranged from 56 to 130. The TTHR per 10,000 ranged from seven to 20. The mean PPTT was 99 (95% CI, 77-122) and the median was 98. The mean TTHR was 16 (95% CI, 12-29) and the median TTHR was 17. Patients presenting from mosh-pits were more frequently male (57.6%; P<.004). The mean age was 20 (95% CI, 19-20). Treatment received was overwhelmingly at the Basic Life Support (BLS) level (96.8%; P<.000001). General moshing was the most common activity leading to injury. Crowd surfing was the next most significant, accounting for 20% of presentations. The most common body part injured was the head (64% of injuries).

This retrospective review of mosh-pit-associated injury patterns demonstrates a high rate of injuries and presentations for medical aid at the evaluated events. General moshing was the most commonly associated activity and the head was the most common body part injured.

MilstenAM, TennysonJ, WeisbergS, Retrospective Analysis of Mosh-Pit-Related Injuries. Prehosp Disaster Med. 2017;32(6):636–641.