team_name: ILM
model_name: EKF
model_abbr: ILM-EKF
model_contributors:
  - name: Stefan Heyder
    email: stefan.heyder@tu-ilmenau.de
  - name: Thomas Hotz
    email: thomas.hotz@tu-ilmenau.de
website_url: https://github.com/Stochastik-TU-Ilmenau
license: cc-by-4.0
team_model_designation: primary
methods: Extended Kalman filter based on reproduction equation
data_inputs: JHU
methods_long: We use the reproduction equation to obtain a state space model whose
  states  comprise incidences, the current reproduction number, the generation time
  distribution,  as well as fraction of deaths by delay. An extended Kalman filter
  is used to fit this model  and obtain forecasts. Quantiles for the latter are obtained
  from a log-normal distribution  with mean and variance given by the prediction steps.