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IntroductionMass 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.ProblemThere 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.

IntroductionMass 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.ProblemWhile 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.