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accelerate_cholera_campaign() accelerate cholera by adding planned cholera campaigns to the provided values in df. When a value is reported for a year and country, then this value is kept, even after 2018. Planned values are provided only for the denominator. For some planned campaigns only the denominator is provided. When this is the case, the numerator is calculated by taking the best historical vaccination coverage achieved, or if not available that the best regional historical coverage.

Usage

accelerate_cholera_campaign(
  df,
  value_col = "value",
  end_year = 2025,
  target_year = end_year,
  start_year = 2018,
  ind_ids = billion_ind_codes("hep"),
  scenario_col = "scenario",
  default_scenario = "default",
  scenario_name = "acceleration",
  ...
)

Arguments

df

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

value_col

Column name of column with indicator values.

end_year

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

target_year

Year by which the scenario should eventually be achieved. Defaults to end_year

start_year

Base year for contribution calculation, defaults to 2018.

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.

default_scenario

name of the default scenario to be used.

scenario_name

Name of the scenario. Defaults to scenario_percent_change_baseline_year

...

additional parameters to be passed to scenario function

Value

data frame with acceleration scenario binded to df. scenario_col is set to acceleration

Details

Planned campaigns are a mix between planned campaigns and the targets outlined in the roadmap 2030 of the Global Task Force on Cholera Control.