| Etablissement | Université 8 mai 1945 de Guelma | | Affiliation | Département d'Electrotechnique et automatique | | Auteur | MENASRIA, Hafidh | | Directeur de thèse | SEBBAGH Abdennour (Professeur) | | Co-directeur | MENASRIA Azzeddine (Maitre de conférence A) | | Filière | Automatique et Informatique Industrielle | | Diplôme | Doctorat LMD | | Titre | Tracking and monitoring of outbreaks using engineering techniques based on epidemiological state models and artificial intelligence | | Mots clés | Epidemiological models, Extended Kalman Filter, outbreaks, artificial intelligence. | | Résumé | The spread of infectious diseases poses a major challenge to global public health, with significant economic, social, and health consequences. Epidemics can emerge rapidly, disrupting healthcare systems and requiring swift and effective responses from health authorities. However, the complexity of these epidemic dynamics, influenced by numerous factors such as human behavior, population mobility, and environmental variations, makes forecasting difficult. The lack of robust analytical tools can lead to delayed or inappropriate decisions, exacerbating the spread and impact of epidemics. Furthermore, public health policies must rely on reliable data and adequate analysis to be effective, which necessitates interdisciplinary collaboration between researchers, policymakers, and the general public. We aim to leverage the latest advances in epidemiological modeling and artificial intelligence to better understand and predict the spread of infectious diseases. By combining these two approaches, we seek to develop tools and methods to more effectively monitor, accurately predict, and better manage epidemics. This research could have a significant impact on public health strategies aimed at controlling and preventing the spread of contagious diseases. | | Statut | Validé |
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