Plot the epidemic doubling time — plot_doubling

Plots the estimated time-varying doubling time from a fitted EpiSewer model.

Usage

plot_doubling_time(
  results,
  median = FALSE,
  seeding = FALSE,
  forecast = TRUE,
  forecast_horizon = NULL,
  date_margin_left = 0,
  date_margin_right = 0,
  facet_models = FALSE,
  facet_direction = "rows",
  base_model = "",
  model_levels = NULL,
  intervals = c(0.5, 0.95)
)

Arguments

results: Results object returned by EpiSewer() after model fitting. Can also be a named list with results from different model runs, in which case all results are plotted together and distinguished by colors.
median: Should the estimated median be shown, or only the credible intervals? Default is FALSE to avoid over-interpretation of the median.
seeding: Should infections from the seeding phase be shown as well? Default is FALSE.
forecast: Should forecasted doubling times be shown? Default is true. This requires that the model was fitted with a forecast horizon, see model_forecast().
forecast_horizon: How many days into the future should forecasts be plotted? Note that this is restricted by the forecast horizon specified during model fitting, see horizon_assume().
date_margin_left: By how many days into the past should the plot be expanded? Can also be negative to cut off some of the earliest dates.
date_margin_right: By how many days into the future should the plot be expanded? Can also be negative to cut off some of the latest dates.
facet_models: Should the plot be faceted by model? Default is FALSE.
facet_direction: How should the facetting be done? Either in different "rows" (default) or in different "columns".
base_model: Name of the base model (in the named list provided to results) which should be compared to the other models. This model will be plotted in black and will not be part of the legend.
model_levels: A character vector with the names of the models to be included. The colors and legend will be ordered according to the order in model_levels.

Value

A ggplot object showing the estimated time-varying doubling time. Can be further manipulated using ggplot2 functions to adjust themes and scales, and to add further geoms.