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[Questioning] Allows users to plot the output from estimate_infections() easily. In future releases it may be depreciated in favour of increasing the functionality of the S3 plot methods.

Usage

plot_estimates(
  estimate,
  reported,
  ylab = "Cases",
  hline,
  obs_as_col = TRUE,
  max_plot = 10,
  estimate_type = NULL
)

Arguments

estimate

A <data.table> of estimates containing the following variables: date, type (must contain "estimate", "estimate based on partial data" and optionally "forecast").

reported

A <data.table> of reported cases with the following variables: date, confirm.

ylab

Character string, defaulting to "Cases". Title for the plot y axis.

hline

Numeric, if supplied gives the horizontal intercept for a indicator line.

obs_as_col

Logical, defaults to TRUE. Should observed data, if supplied, be plotted using columns or as points (linked using a line).

max_plot

Numeric, defaults to 10. A multiplicative upper bound on the\ number of cases shown on the plot. Based on the maximum number of reported cases.

estimate_type

Character vector indicating the type of data to plot. Default to all types with supported options being: "Estimate", "Estimate based on partial data", and "Forecast".

Value

A ggplot2 object

Examples

# get example model results
out <- readRDS(system.file(
    package = "EpiNow2", "extdata", "example_estimate_infections.rds"
))

# plot infections
plot_estimates(
  estimate = out$summarised[variable == "infections"],
  reported = out$observations,
  ylab = "Cases", max_plot = 2
) + ggplot2::facet_wrap(~type, scales = "free_y")


# plot reported cases estimated via Rt
plot_estimates(
  estimate = out$summarised[variable == "reported_cases"],
  reported = out$observations,
  ylab = "Cases"
)


# plot Rt estimates
plot_estimates(
  estimate = out$summarised[variable == "R"],
  ylab = "Effective Reproduction No.",
  hline = 1
)


#' # plot Rt estimates without forecasts
plot_estimates(
  estimate = out$summarised[variable == "R"],
  ylab = "Effective Reproduction No.",
  hline = 1, estimate_type = "Estimate"
)