The COVID-19 pandemic is a global pandemic of coronavirus disease caused by SARS-CoV-2. Governments are taking a wide range of non-pharmaceutical interventions (NPIs) in response to the COVID-19 outbreak. These measures include interventions as stringent as strict lockdown to school closings, bars and restaurants closings, curfews and barrier gesture such as masks wearing and social distanciation. Distinguish the effectiveness of each NPI is crucial to inform future preparedness response plans. We propose an approach which focuses on French data and combines estimation of epidemics dynamics models and estimation of NPIs effectiveness. We develop a multi-level model of the French COVID-19 epidemic at the regional level relying on a global extended Susceptible-Exposed-Infectious-Recovered (SEIR) model as a simplified representation of the average epidemic process. We estimate the transmission rate with a population Kalman filter using hospitalization data from the SIVIC database over a period of one year (March 2020 to 2021). Then we infer the linear relationship between transmission rate and NPIs introduction allowing to estimate the effect of non-pharmaceutical interventions adjusting for weather, vaccination and apparition of more transmissible variants.