team_name: epiMOX
model_name: SUIHTER
model_abbr: epiMOX-SUIHTER
model_contributors: Giovanni Ardenghi (Politecnico di Milano) <giovanni.ardenghi@polimi.it>, Giovanni Ziarelli (Politecnico di Milano) <giovanni.ziarelli@polimi.it>, Luca Dede' (Politecnico di Milano) <luca.dede@polimi.it>, Nicola Parolini (Politecnico di Milano) <nicola.parolini@polimi.it>, Alfio Quarteroni (Politecnico di Milano, EPFL) <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
institution_affil: MOX, Dipartimento di Matematica, Politecnico di Milano