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How the Italian Formula 1 Grand Prix 2022 Mass Gathering Event Compares to the Arbon Model: A Descriptive Study

Published online by Cambridge University Press:  21 July 2023

Andrea Paleari ,
Stefano Spina Open the ORCID record for Stefano Spina [Opens in a new window] ,
Francesco Marrazzo Open the ORCID record for Francesco Marrazzo [Opens in a new window] ,
Alba Ripoll ,
Fabio Volontè ,
Gianluca Greco ,
Alberto Zoli ,
Giuseppe Maria Sechi ,
Diego Saggiante  and
Gianluca Chiodini
...Show all authors
Andrea Paleari
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Stefano Spina
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, Niguarda Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
Francesco Marrazzo
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, Niguarda Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
Alba Ripoll
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, Niguarda Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy Research Centre in Emergency and Disaster Medicine (CRIMEDIM), Università del Piemonte Orientale, Novara, Italy
Fabio Volontè
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Gianluca Greco
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, San Gerardo Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Alberto Zoli
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Giuseppe Maria Sechi
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Diego Saggiante
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Gianluca Chiodini
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy
Riccardo Stucchi
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, Niguarda Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
Roberto Fumagalli*
Affiliation:
Agenzia Regionale Emergenza Urgenza (AREU), Milan, Lombardy, Italy Department of Anesthesia, Critical Care and Pain Medicine, Niguarda Hospital, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
*
Corresponding author: Roberto Fumagalli; Email: roberto.fumagalli@unimib.it.
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Abstract

Objective:

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.

Methods:

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).

Results:

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.

Conclusions:

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.

Keywords

Formula 1EMSmass gathering eventpatient presentation rateArbon Model
Type
Concepts in Disaster Medicine
Information
Disaster Medicine and Public Health Preparedness , Volume 17 , 2023 , e468
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Society for Disaster Medicine and Public Health

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