team_name: epiMOX model_name: SUIHTER model_abbr: epiMOX-SUIHTER model_contributors: - name: Giovanni Ardenghi affiliation: Politecnico di Milano email: giovanni.ardenghi@polimi.it - name: Giovanni Ziarelli affiliation: Politecnico di Milano email: giovanni.ziarelli@polimi.it - name: Luca Dede' affiliation: Politecnico di Milano email: luca.dede@polimi.it - name: Nicola Parolini affiliation: Politecnico di Milano email: nicola.parolini@polimi.it - name: Alfio Quarteroni affiliation: Politecnico di Milano, EPFL email: alfio.quarteroni@polimi.it website_url: https://www.epimox.polimi.it license: mit team_model_designation: primary methods: Compartmental model SUIHTER methods_long: 'The results are obtained using the compartmental model SUIHTER which simulates the evolution of COVID-19 epidemic in Italy. SUIHTER comprises the following compartments: Susceptibles(S), Undetected(U), Isolated(I), Hospitalized(H), Threatened(T), Extinct(E), Recovered(R). The model parameters are calibrated thanks to a combination of the least squares method with the Markov Chain Monte Carlo (MCMC) method. The current version of the model accounts for two additional compartments collecting individuals who have received the first and the second dose of vaccine, respectively. Different NPIs and vaccination scenarios can be accounted for in the model forecast.' citation: https://doi.org/10.1098/rspa.2021.0027