View source: R/accelerate_target_uhc.R
accelerate_target_uhc_tobacco | R Documentation |
Accelerate uhc_tobacco by first dividing countries into two groups:
For countries without any routine (i.e., estimated) data, business as usual is returned
For countries with routine (i.e., estimated) data, the best of business as usual and a percent decrease of 30% between 2010 and 2025 is returned. Both scenarios are run on the crude tobacco usage values, which are then converted to their age-standardised equivalents using an approximation.
accelerate_target_uhc_tobacco(
df,
ind_ids = billion_ind_codes("uhc"),
scenario_col = "scenario",
value_col = "value",
end_year = 2025,
start_year = 2018,
default_scenario = "default",
bau_scenario = "historical",
scenario_name = "acceleration",
...
)
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
|
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 |
end_year |
End year(s) for contribution calculation, defaults to 2019 to 2025. |
start_year |
Year from which the acceleration scenario begins, inclusive. |
default_scenario |
name of the default scenario. |
bau_scenario |
name of scenario to be used for business as usual.
Default is |
scenario_name |
name of scenario |
... |
additional parameters to be passed to scenario function |
Target scenario
accelerate_target_anc4()
,
accelerate_target_art()
,
accelerate_target_beds()
,
accelerate_target_bp()
,
accelerate_target_doctors()
,
accelerate_target_dtp3()
,
accelerate_target_fh()
,
accelerate_target_fpg()
,
accelerate_target_fp()
,
accelerate_target_hwf()
,
accelerate_target_itn()
,
accelerate_target_nurses()
,
accelerate_target_pneumo()
,
accelerate_target_tb()
,
accelerate_target_uhc_sanitation()
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