Machine Learning-Based Prediction of Heatwave-Related Hospitalizations: A Case Study in Matam, Senegal

Mory Toure (), Ibrahima Sy, Ibrahima Diouf, Ousmane Gueye, Endalkachew Bekele, Md Abul Ehsan Bhuiyan, Marie Jeanne Sambou, Papa Ngor Ndiaye, Wassila Mamadou Thiaw, Daouda Badiane, Aida Diongue-Niang, Amadou Thierno Gaye, Ousmane Ndiaye and Adama Faye
Additional contact information
Mory Toure: Agence Nationale de l’Aviation Civile et de la Météorologie (ANACIM), Dakar BP 8184, Senegal
Ibrahima Sy: Ministère de la Santé et de l’Action Sociale, Dakar BP 4024, Senegal
Ibrahima Diouf: Laboratoire de Physique de l’Atmosphère et de l’Ocean–Simeon Fongang (LPAO-SF), Ecole Superieure Polytechnique, Universite Cheikh Anta Diop (UCAD), Dakar BP 5085, Senegal
Ousmane Gueye: Centre Hospitalier Régional El Hadji Ibrahima Niass (CHREIN), Kaolack BP 24030, Senegal
Endalkachew Bekele: National Center for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), College Park, MD 20740, USA
Md Abul Ehsan Bhuiyan: National Center for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), College Park, MD 20740, USA
Marie Jeanne Sambou: Laboratoire de Physique de l’Atmosphère et de l’Ocean–Simeon Fongang (LPAO-SF), Ecole Superieure Polytechnique, Universite Cheikh Anta Diop (UCAD), Dakar BP 5085, Senegal
Papa Ngor Ndiaye: Agence Nationale de l’Aviation Civile et de la Météorologie (ANACIM), Dakar BP 8184, Senegal
Wassila Mamadou Thiaw: National Center for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), College Park, MD 20740, USA
Daouda Badiane: Laboratoire de Physique de l’Atmosphère et de l’Ocean–Simeon Fongang (LPAO-SF), Ecole Superieure Polytechnique, Universite Cheikh Anta Diop (UCAD), Dakar BP 5085, Senegal
Aida Diongue-Niang: Agence Nationale de l’Aviation Civile et de la Météorologie (ANACIM), Dakar BP 8184, Senegal
Amadou Thierno Gaye: Laboratoire de Physique de l’Atmosphère et de l’Ocean–Simeon Fongang (LPAO-SF), Ecole Superieure Polytechnique, Universite Cheikh Anta Diop (UCAD), Dakar BP 5085, Senegal
Ousmane Ndiaye: African Center of Meteorological Applications for Development (ACMAD), Niamey BP 13184, Niger
Adama Faye: Institut de Santé et Développement (ISED), Université Cheikh Anta Diop (UCAD), Dakar BP 5005, Senegal

IJERPH, 2025, vol. 22, issue 9, 1-22

Abstract: This study assesses the impact of heatwaves on hospital admissions in the Matam region of Senegal by combining climatic indices with machine learning methods. Using daily maximum temperature (TMAX) and heat index (HI), heatwave events were identified from 2017 to 2022. Hospital data from Ourossogui Regional Hospital were analyzed, and three predictive models, Random Forest (RF), Extreme Gradient Boosting (XGB), and Generalized Additive Models (GAMs), were compared. A bootstrapping approach with 1000 iterations was used to evaluate model robustness. The findings reveal a significant delayed effect of heatwaves, with increased hospitalizations occurring three to five days after the event. RF outperformed the other models with R 2 values ranging from 0.51 to 0.72. These findings highlight the need to enhance heatwave monitoring and promote the integration of impact-based climate forecasting into health early warning systems, particularly to protect vulnerable groups such as the elderly, children, and outdoor workers.

Keywords: heatwave; hospital admissions; machine learning; climate-health; early warning systems; Senegal (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2025
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