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Published online by Cambridge University Press: 13 July 2023
Mass gatherings are becoming increasingly more common and require adequate preparedness in order to ensure the safety of participants. Standardized planning tools for optimal resource utilization during these events are lacking. We analyzed prehospital data from a high census US theme park to determine whether heat index and wet bulb index are predictive of patient presentation and transport rates.
This was a retrospective analysis of prehospital data from a high census US theme park. Daily EMS data including call and transport volume as well as corresponding local weather information were gathered between May 2021 to September 2022. The relationship between patient presentation rate and transport rate and weather information was analyzed using Analysis of Variance Testing. Patient presentation rates were calculated based on average daily attendance according to unofficial attendance tracking sources. Seasonal attendance variation was accounted for by comparing variations in patient presentation and transports to the average call and transportations rates for that respective month.
A total of 515 days of data were included. We found that higher wet bulb temperature readings correlated with both higher patient presentation rates per 10,000 attendees (>80F 4.09, 70-79F 3.39, <69F 2.84 patients; P<0.05) and increased hospital transport rates per 10,000 attendees (>80F 1.38, 70-79F 1.29, <69F 1.09 patients; P<0.05). Adjusted for seasonal variation of attendance, higher wet bulb temperatures were likewise correlated with increased presentation (>80F 102%, 70-79F 98%, <69F 93% of average patients per day; P<0.05) and transports (>80F 101%, 70-79F 100%, <69F 93% of average transports per day; P<0.05). Additional analysis noted similarly increased patient presentation and transport rates on days with higher maximum heat indices.
In the setting of a high census US theme park, higher wet bulb and heat indices were strongly associated with increased patient presentation rates and patient transport rates.