Skip to contents

Get ITHIM-results into correct format for VoI analysis

Source: R/extract_data_for_voi.R
extract_data_for_voi.Rd

This function extracts the relevant information from the multi_city_ithim object and gets the results into the correct format for further analysis.

Usage

extract_data_for_voi(
  NSCEN,
  NSAMPLES,
  SCEN_SHORT_NAME,
  cities,
  output_version,
  level1,
  level2,
  level3
)

Arguments

NSCEN

number of scenarios (not incl. baseline)

NSAMPLES

number of model runs per city

SCEN_SHORT_NAME

names of the scenarios (incl. baseline)

cities

list of cities for which the model was run

output_version

the output version of the model run

level1

list of diseases considered in level 1

level2

list of diseases considered in level 2

level3

list of diseases considered in level 3

multi_city_ithim

list containing the ithim model information including results for the various model runs

Value

ithim_results list with the following objects:

voi_complete - dataframe for all cities with all total YLL outcomes for all model runs, age and sex categories and disease and scenario combinations - combined AP and PA pathway

voi_complete_summary - summary statistics of YLLs for combined AP and PA pathway

voi_complete_100k - dataframe for all cities for all YLL outcomes per 100k - combined AP and PA pathway

voi_commplete_100k_summary - summary statistics per of YLL per 100k for combined AP and PA pathway

voi_complete_pathway - dataframe for all cities with all total YLL outcomes for all model runs, age and sex categories and disease and scenario combinations - separate AP and PA pathways

voi_complete_summary_pathway - summary statistics of YLLs for separate AP and PA pathways

voi_complete_100k_pathway - dataframe for all cities for all YLL outcomes per 100k - separate AP and PA pathways

voi_commplete_100k_summary_pathway - summary statistics per of YLL per 100k for separate AP and PA pathways

Details

The function performs the following steps:

  • by looping through the cities:

    • extract the population statistics

    • create one dataframe for all cities with all outcomes for all model runs, age and sex groups and disease and scenario combinations for the combined AP and PA results

    • create one dataframe for all cities with all outcomes for all model runs, age and sex groups and disease and scenario combinations for the separate AP and PA results

  • compute statistics (mean, 2.5th and 97.5th percentiles, standard deviation) for total YLLs lost for the combined AP and PA results

  • compute statistics (mean, 2.5th and 97.5th percentiles, standard deviation) for YLLs lost per 100k for the combined AP and PA results

  • compute statistics (mean, 2.5th and 97.5th percentiles, standard deviation) for total YLLs lost for the separate AP and PA pathways

  • compute statistics (mean, 2.5th and 97.5th percentiles, standard deviation) for YLLs lost per 100k for the separate AP and PA pathways