team_name: Epiforecasts / London School of Hygiene and Tropical Medicine
model_name: EpiExpert Rt (epiforecasts)
model_abbr: epiforecasts-EpiExpert_Rt
model_contributors: Nikos Bosse <nikos.bosse@lshtm.ac.uk>, Sam Abbott <sam.abbott@lshtm.ac.uk>, Sebastian Funk
website_url: https://epiforecasts.io/
license: mit
team_model_designation: other
methods: Mean ensemble of human predictions of Rt which get mapped to cases and deaths using a renewal equation
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 of Rt from experts and non-experts are elicited using a shinyApp. \
  \ Individuals choose a distribution (default is normal) for Rt and change the \
  \ median and width of that predictive distribution for evey forecast horizon. \
  \ Based on individual forecasts, samples are drawn from the individual forecast \
  \ distributions. These samples are used to simulate cases and deaths based on a \
  \ renewal equation using the R package EpiNow2."