Abstract: Compartmental epidemic models were critical in the COVID-19 pandemic, especially when decisions had to be made quickly and evidence was limited. Due to the increasing demands for modeling complex systems, designing optimal control, and conducting optimization tasks for short and long terms, epidemic models are lately receiving growing attention. In general, there are two types of mathematical models: deterministic and stochastic. There is no uncertainty in deterministic models. Stochastic models, on the other hand, take into account the elements of hazard and chance. In this talk, many aspects in stochastic mathematical modelling will be presented. Also, a description for some characteristics such as a temporary immunity, relapsing infectious diseases, different saturation factors and public health control strategies using stochastic stability analysis and stochastic optimal control.

Bio: Dr. Idriss SEKKAK is working as a Postdoctoral follow at Ecole de Santé Publique, Montreal University and in the Mathematics for public health program at the Fields institute for research and mathematical sciences (Supervised by Prof. Bouchra Nasri), where he develops an integrative framework that explores the impact of public health interventions across a broad spectrum of societal and economic issues. he received his Ph.D. degree in stochastic modeling and control strategies in epidemiology from the University of Ibn Tofail, Kénitra, Morocco. His main research interests include dynamical systems, stochastic analysis, stochastic optimization, and their applications.