Accelerate art by first dividing countries into those with reported data and those without.
For countries without reported data, business as usual is returned.
For countries with reported data, the best of business as usual and fixed target of 95% by 2025 is chosen.
Usage
accelerate_art(
df,
ind_ids = billion_ind_codes("uhc"),
scenario_col = "scenario",
value_col = "value",
start_year = 2018,
end_year = 2025,
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
Name of the column containing indicator value in
df.- start_year
Year from which the acceleration scenario begins, inclusive.
- end_year
End year(s) for contribution calculation, defaults to 2019 to 2025.
- 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_beds(),
accelerate_bp(),
accelerate_doctors(),
accelerate_dtp3(),
accelerate_fh(),
accelerate_fpg(),
accelerate_fp(),
accelerate_hwf(),
accelerate_itn(),
accelerate_nurses(),
accelerate_pneumo(),
accelerate_tb(),
accelerate_uhc_sanitation(),
accelerate_uhc_tobacco()