team_name: Epiforecasts / London School of Hygiene and Tropical Medicine
model_name: EpiExpert (epiforecasts)
model_abbr: epiforecasts-EpiExpert
model_contributors:
  - name: Nikos Bosse
    email: nikos.bosse@lshtm.ac.uk
  - name: Sam Abbott
    email: sam.abbott@lshtm.ac.uk
  - name: Sebastian Funk
website_url: https://epiforecasts.io/
license: mit
team_model_designation: primary
methods: Mean ensemble of human predictions
team_funding: Funding by the Health Protection Research Unit (grant code NIHR200908)
data_inputs: ECDC deaths and cases
citation: https://github.com/epiforecasts/covid-german-forecasts
methods_long: Forecasts from experts and non-experts are elicited using a shinyApp.  Two
  variants of this shiynApp exist. In one, forecasters are asked to predict  cases
  and deaths directly. In the other, forecasters are asked to predict Rt.  The Rt
  predictions are then mapped to death and cases using a renewal equation  and the
  R package EpiNow2.  Individuals currently make forecasts by choosing a distribution
  and specifying the  median and width of that predictive distribution for evey forecast
  horizon.  Forecasts from both apps are collected and a mean ensemble is formed.