team_name: KITmetricslab
model_name: bivar_branching
model_abbr: KITmetricslab-bivar_branching
model_contributors:
  - name: Johannes Bracher
    affiliation: Karlsruhe Institute of Technology
    email: johannes.bracher@kit.edu
website_url: https://github.com/jbracher/branching_process_delta
license: cc-by-4.0
team_model_designation: primary
methods: Delta-variant and other cases are modelled as independent branching processes,
  with weekly growth\ \ rates following random walks. Forecasts for 3 and 4 wk are
  likely unreliable.
team_funding: Helmholtz Innovation and Data Science Project "SIMCARD"
data_inputs: JHU (confirmed cases), RKI sequencing data (variants)
methods_long: The total weekly incidence is modelled as the sum of two independent
  overdispersed branching processes (delta / non-delta cases; may be updated to other
  pairs of variants later), with the weekly  growth rates following multiplicative
  random walks. Sequencing data are included via an additional binomial observation
  process with the probabilities for the two variants proportional to their occurrence
  in the two  latent branching processes. Posterior samples are generated using the
  JAGS software. Priors were chosen as 'uninformative' uniform distributions, but
  may be specified in a more informative fashion in the future. In order to be included
  in the ensemble forecasts are generated up to 4 wk into the future, but given the
  simple model structure, three and four-week-ahead forecasts should be interpreted
  with caution.