regional_summary {EpiNow2}

Regional Summary Output

Description

Used to produce summary output either internally in regional_epinow or externally.

Usage

regional_summary(
  regional_output = NULL,
  reported_cases,
  results_dir = NULL,
  summary_dir = NULL,
  target_date = NULL,
  region_scale = "Region",
  all_regions = TRUE,
  return_output = FALSE,
  plot = TRUE,
  max_plot = 10,
  ...
)

Arguments

regional_output

A list of output as produced by regional_epinow and stored in the regional list.

reported_cases

A data frame of confirmed cases (confirm) by date (date), and region (region).

results_dir

An optional character string indicating the location of the results directory to extract results from.

summary_dir

A character string giving the directory in which to store summary of results.

target_date

A character string giving the target date for which to extract results (in the format "yyyy-mm-dd"). Defaults to latest available estimates.

region_scale

A character string indicating the name to give the regions being summarised.

all_regions

Logical, defaults to TRUE. Should summary plots for all regions be returned rather than just regions of interest.

return_output

Logical, defaults to FALSE. Should output be returned, this automatically updates to TRUE if no directory for saving is specified.

plot

Logical, defaults to TRUE. Should regional summary plots be produced.

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.

...

Additional arguments passed to report_plots.

Value

A list of summary measures and plots

See Also

regional_epinow

Examples

# example delays
generation_time <- get_generation_time(
 disease = "SARS-CoV-2", source = "ganyani"
)
incubation_period <- get_incubation_period(
 disease = "SARS-CoV-2", source = "lauer"
)
reporting_delay <- estimate_delay(rlnorm(100, log(6), 1), max_value = 30)

# example case vector from EpiSoon
cases <- example_confirmed[1:30]
cases <- data.table::rbindlist(list(
  data.table::copy(cases)[, region := "testland"],
  cases[, region := "realland"]
))

# run basic nowcasting pipeline
out <- regional_epinow(
  reported_cases = cases,
  generation_time = generation_time_opts(generation_time),
  delays = delay_opts(incubation_period + reporting_delay),
  output = "region",
  rt = NULL
)

regional_summary(
  regional_output = out$regional,
  reported_cases = cases
)