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