team_name: epiforecasts
model_name: weeklygrowth
model_abbr: epiforecasts-weeklygrowth
model_contributors:
  - name: Sam Abbott
    affiliation: Centre for Mathematical Modelling, London School of Hygiene and Tropical Medicine
    email: sam.abbott@lshtm.ac.uk
website_url: https://samabbott.co.uk
license: mit
team_model_designation: secondary
methods: A Bayesian autoregressive model using weekly incidence data, application
  of the forecast.vocs R package.
data_inputs: Reported cases by date of report aggregated to weeks.
citation: none
methods_long: A Bayesian autoregressive model using weekly incidence data designed
  to run as a Github action. Both cases and the growth rate are assumed to be AR(1)
  processes with the growth rate being differenced and scaled by a decay parameter.
  The model is implemented using the forecast.vocs R package (https://epiforecasts.io/forecast.vocs).
  The analysis code is available at https://github.com/seabbs/ecdc-weekly-growth-forecasts