| Name: | bivariate_branching |
|---|---|
| Abbreviation: | KITmetricslab-bivariate_branching |
| Owner: | epiforecasts |
| Team name: | KITmetricslab |
| Description: | Delta-variant and other cases are modelled as independent branching processes, with weekly growth\ \ rates following random walks. Vaccination progress is currently not included.\ \ Forecasts up to 4 wk are generated due to ensemble inclusion requirements, but 3 and 4 wk should be\ \ interpreted with great caution. |
| Contributors: | Johannes Bracher (Karlsruhe Institute of Technology) <johannes.bracher@kit.edu> |
| License: | Creative Commons Attribution 4.0 |
| Notes: | primary |
| Citation: | NA |
| Methods: | 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 enerated 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. |
| Home: | https://github.com/jbracher/branching_process_delta |
| Auxiliary data: | NA |
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