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# Using machine learning to predict drownings in surf beaches of southwest France

David Carayon, Bruno Castelle, Eric Tellier, Bruno Simmonet, Jeoffrey Dehez

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## To cite this version:

David Carayon, Bruno Castelle, Eric Tellier, Bruno Simmonet, Jeoffrey Dehez. Using machine learning to predict drownings in surf beaches of southwest France. World Conference on Drowning Prevention, Surf Life Saving Australia; Life Saving Society Australia, Dec 2023, Perth (Australia), Australia. hal-04342633

HAL Id: hal-04342633

https://hal.inrae.fr/hal-04342633

Submitted on 13 Dec 2023

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Open licence - etalab
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World Conference on
Drowning Prevention

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# Using machine learning to predict drownings in surf beaches of southwest France

**David**
**Carayon**¹

¹INRAE | ETTIS Research Unit

Bruno
Castelle²

²CNRS | EPOC Research Unit

Eric
Tellier³

³INSERM | AheaD Research Unit

Bruno
Simmonet⁴

⁴Bordeaux University Hospital

Jeffrey
Dehez¹

¹INRAE | ETTIS Research Unit
Some context

Should France be your next vacation
destination 🌿 ?

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Southwest France :
The place to be 😂

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# Some (scary 😞) numbers

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* One of the most dangerous coasts in the world (Castelle et al. 2019) : heavy rip current (Baïnes), shore break

* Surveillance mainly during summer : Thousands of rescues each year

* 20 to 30 fatal drownings each year (0 between the flags)

* About 1/2 of swimmers bathe outside of the surveillance zone (Dehez and Lyser 2021)
Can we prevent
drownings ?

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Can we prevent
predict drownings ?

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# Goal of this work

* Same philosophy as previous work (Tellier et al. 2021) : Daily emergency calls prediction based on weather and beach crowd

* Better (and cleaner) data

* New statistical methods

* The SWYM Project

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SURF ZONE HAZARDS
RECREATIONAL BEACH USE
& WATER SAFETY MANAGEMENT
# Predicting drownings using Machine Learning

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# Predictors and
outcome

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## OUTCOME

* Water inhalation & respiratory impairments which lead to **emergency calls**

Binary daily data
2011-2022

$$ \text{Risk} = \text{Hazard} * \text{Exposure} $$

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## PREDICTORS

* Wave Incidence Factor (cos4h)

* Wave Factor (HsTp)

* Air temperature

* Day (ex : 6 for 6th of July)

* Month

* Wday (ex : 1 for Monday)
# Modelling workflow

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## Data pre-processing

- Centering, scaling, dummy-coding

- Synthetic Minority Over-sampling Technique (SMOTE) (Chawla et al. 2002) for the outcome
# Modelling workflow

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# Modelling workflow

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# Our winner : XGBoost

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0.9 [0.89-0.91]
Area Under the Curve (AUC)

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0.88 [0.87-0.89]
Accuracy

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0.49 [0.41-0.55]
Positive Predictive Value
(PPV)

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0.96 [0.95-0.99]
Negative Predictive Value
(NPV)

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Probability discretization :
Making Risk classes

<table><thead><tr><td>Risk class</td><td># of Drownings</td><td># of "No Drownings"</td><td>Total</td></tr></thead><tbody><tr><td>1</td><td>31</td><td>502</td><td>533</td></tr><tr><td>2</td><td>20</td><td>44</td><td>64</td></tr><tr><td>3</td><td>4</td><td>20</td><td>24</td></tr><tr><td>4</td><td>16</td><td>11</td><td>27</td></tr><tr><td>5</td><td>7</td><td>8</td><td>15</td></tr></tbody></table>

N = 663 testing set
Discussion

“all models are wrong, but some are useful”

George Box

➤ What is the best **drowning prediction model** ? Lowering false negatives or false positives ? → Risk management and political decisions

➤ Low improvements over previous models → dataset limitation ?

➤ Emergency call database only covers a **minority** 😞 of all rescues
# Perspectives

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Majority of rescues

iPad data collection
offline mode available

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New Model !

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Monitoring Dashboard

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Database

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Thank you!

Want to try this at home?

Interested in the technical stuff?

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Contact us :

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david.carayon@inrae.fr

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@david_carayon

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quarto

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tidyverse

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DrowningAlert

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tidymodels

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targets

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renv

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CHEERS MATE!
References

Castelle, Bruno, Tim Scott, Rob Brander, Jak McCarroll, Arthur Robinet, Eric Tellier, Elias de Korte, Bruno Simonnet, and Louis-Rachid Salmi. 2019. "Environmental Controls on Surf Zone Injuries on High-Energy Beaches." *Natural Hazards and Earth System Sciences* 19 (10): 21832205.

Chawla, N. V., K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer. 2002. "SMOTE: Synthetic Minority over-Sampling Technique." *Journal of Artificial Intelligence Research* 16 (June): 321–57. https://doi.org/10.1613/jair.953.

Dehez, Jeoffrey, and Sandrine Lyser. 2021. "Fréquentation des plages océanes et risques de baignade en Aquitaine en 2020. Une étude exploratoire." *Research Report. INRAE*. https://hal.science/hal-03549020.

Sacks, Jerome, William J. Welch, Toby J. Mitchell, and Henry P. Wynn. 1989. "Design and Analysis of Computer Experiments." *Statistical Science* 4 (4). https://doi.org/10.1214/ss/1177012413.

Tellier, Éric, Bruno Simonnet, Cédric Gil-Jardiné, Marion Lerouge-Bailhache, Bruno Castelle, and Rachid Salmi. 2021. "Predicting Drowning from Sea and Weather Forecasts: Development and Validation of a Model on Surf Beaches of Southwestern France." *Injury Prevention* 28 (1): 16–22. https://doi.org/10.1136/injuryprev-2020-044092.