To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
Email your librarian or administrator to recommend adding this to your organisation's collection.