Scenario return to previpus trajectory

This scenario returns to the scenario_previous_trajectory after the last value of scenario_shock.

Usage

scenario_return_previous_trajectory(
  df,
  dip_year = 2020,
  recovery_year = 2022,
  start_year = 2018,
  end_year = 2025,
  value_col = "value",
  scenario_col = "scenario",
  scenario_name = "return_previous_trajectory",
  scenario_shock = "covid_shock",
  scenario_previous_trajectory = "pre_covid_trajectory",
  trim = TRUE,
  small_is_best = FALSE,
  keep_better_values = FALSE,
  upper_limit = 100,
  lower_limit = 0,
  trim_years = TRUE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  source = sprintf("WHO DDI, %s", format(Sys.Date(), "%B %Y"))
)

Arguments

df

Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.

dip_year

(integer) year where the dip appends

recovery_year

(integer) year from which the AROC will be applied

start_year

Base year for contribution calculation, defaults to 2018.

end_year

End year(s) for contribution calculation, defaults to 2019 to 2025.

value_col

Column name of column with indicator values.

scenario_col

(character) name of the column with the scenarios.

scenario_name

name of scenario

scenario_shock

(character) name of the scenario with the shock

scenario_previous_trajectory

(character) name of the scenario with the previous trajectories.

trim

logical to indicate if the data should be trimmed between upper_limit and lower_limit.

small_is_best

Logical to identify if a lower value is better than a higher one (e.g. lower obesity in a positive public health outcome, so obesity rate should have small_is_best = TRUE).

keep_better_values

logical to indicate if "better" values should be kept from value_col if they are present. Follows the direction set in small_is_best. For instance, if small_is_best is TRUE, then value_col lower than col will be kept.

upper_limit

upper limit at which the indicator should be caped.

lower_limit

lower_limit limit at which the indicator should be caped.

trim_years

logical to indicate if years before start_year_trim and after end_year_trim should be removed

start_year_trim

(integer) year to start trimming from.

end_year_trim

(integer) year to end trimming.

source

Source to provide for calculated average service coverage and single measure.

See also

COVID scenarios scenario_covid_delayed_return(), scenario_covid_never_return(), scenario_covid_rapid_return(), scenario_covid_sustained_disruption(), scenario_dip_recover()