Predicting individual’s decision to enter the water at a high-energy recreational surf beach in France
Beachgoer exposure on any given day can ultimately be predicted by coupling our model with beach attendance models. This would allow for the design of rescue and preventive operations on days with high expected exposure. While models based solely on environmental factors can be used to forecast beach risks, incorporating human factors into the model provides valuable insight for crafting prevention messages. In this regard, lifeguards could engage more actively with beach users to deliver appropriate safety messages.
Authors
- Jeoffrey Dehez (ORCID: https://orcid.org/0000-0003-2604-8937)
- Bruno Castelle (ORCID: https://orcid.org/0000-0003-1740-7395)
- Sandrine Lyser (ORCID: https://orcid.org/0000-0001-6820-0672)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université de Bordeaux (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Environnements et Paléoenvironnements Océaniques et Continentaux (FR)
- UMR BIOdiversity, GEnes & Communities (FR)
- Institut Polytechnique de Bordeaux (FR)
Publication Details
- Journal
- Injury Prevention
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1136/ip-2024-045574
- Citations
- 3
- Primary Topic
- Injury Epidemiology and Prevention
- Type
- article
- Field-Weighted Citation Impact
- 5.64
Funders
- Université de Bordeaux
- Conseil Régional Aquitaine