accelerate_hwf: Accelerate hwf

In gpw13/billionaiRe: Calculate the WHO Triple Billions

Accelerate hwf

Description

Accelerate hwf by first dividing countries into two groups:

• For countries with a 2018 value greater than or equal to the 2018 global median, business as usual is returned.

• For countries with a 2018 value less than the 2018 global median, the average of the top 5 rate of change within all countries.

Usage

accelerate_hwf(
  df,
  ind_ids = billion_ind_codes("uhc"),
  scenario_col = "scenario",
  value_col = "value",
  start_year = 2018,
  default_scenario = "default",
  bau_scenario = "historical",
  scenario_name = "acceleration",
  ...
)

Arguments

df	Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
ind_ids	Named vector of indicator codes for input indicators to the Billion. Although separate indicator codes can be used than the standard, they must be supplied as a named vector where the names correspond to the output of billion_ind_codes().
scenario_col	Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.
value_col	Column name of column with indicator values.
start_year	Base year for contribution calculation, defaults to 2018.
default_scenario	name of the default scenario.
bau_scenario	name of scenario to be used for business as usual. Default is historical.
scenario_name	name of scenario
...	additional parameters to be passed to scenario function

See Also

UHC acceleration scenarios accelerate_anc4(), accelerate_art(), accelerate_beds(), accelerate_bp(), accelerate_doctors(), accelerate_dtp3(), accelerate_fh(), accelerate_fpg(), accelerate_fp(), accelerate_itn(), accelerate_nurses(), accelerate_pneumo(), accelerate_tb(), accelerate_uhc_sanitation(), accelerate_uhc_tobacco()

gpw13/billionaiRe documentation built on April 17, 2025, 12:54 p.m.