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.