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Author: icogswell

Brain Health Initiative/Foregone wages of informal caregivers/1 Modeling condition-specific caregiving hours/01_create_age_matrix.R

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+#################################################################
+# Title:    02_create_disability_weights_all_ages.R
+# Author: USERNAME
+# Date: 2024 12 31
+# Project:  BHI - Brain Health Initiative
+# Purpose : Pull YLDs and prevalent cases from the GBD and 
+#           calculate disability weights for brain health causes
+#################################################################
+
+# Setting up environment
+# clear environment
+rm(list = ls())
+
+# packages
+library(data.table)
+
+# file paths
+age_group_id_path <- "FILEPATH/age_group_id_table.csv"
+
+# functions
+source("FILEPATH/get_location_metadata.R")
+source("FILEPATH/get_age_metadata.R")
+source("FILEPATH/get_outputs.R")
+
+# Importing Age group info
+age_group_id_table <- fread(age_group_id_path)
+
+# Data info
+data_yr <- 2021
+gbd_release_id <- 16
+years <- 2000:(data_yr)
+locs <- get_location_metadata(location_set_id = 35, release_id = gbd_release_id)[level == 3]
+ages <- get_age_metadata(age_group_set_id = 24, release_id = gbd_release_id)
+
+####----# Pull and process burden data #----####
+cat(' Pull and process burden data\n')
+
+## Pull YLD values
+burden <- get_outputs('cause',
+                      cause_id = c(332,    #  meningitis
+                                   337,    #  encephalitis
+                                   477,    #  neo_brain
+                                   494,    #  cvd_stroke
+                                   543,    #  neuro_dementia
+                                   544,    #  neuro_parkinsons
+                                   545,    #  neuro_epilepsy
+                                   546,    #  neuro_ms
+                                   554,    #  neuro_neurone
+                                   557,    #  neuro_other
+                                   559,    #  mental_schizo
+                                   567,    #  mental_unipolar
+                                   570,    #  mental_bipolar
+                                   571,    #  mental_anxiety
+                                   572,    #  mental_eating
+                                   575,    #  mental_pdd
+                                   578,    #  mental_adhd
+                                   579,    #  mental_conduct
+                                   582,    #  mental_id
+                                   585,    #  mental_other
+                                   560,    #  mental_alcohol
+                                   562,    #  mental_drug_opioids
+                                   563, 564, 565, 566,    #  mental_drug_other (other substances to aggregate together)
+                                   718,    #  inj_suicide
+                                   972),   #  neuro_headach
+                      location_id = c(1, locs[level == 3]$location_id), # global and country locations
+                      year_id = years, # years 2000 to 2021
+                      sex_id = 3, # both sexes
+                      age_group_id = 22, # all ages
+                      measure_id = c(3, 5), # prevalence and YLDs
+                      metric_id = 1, # numeric
+                      release_id = gbd_release_id)
+
+# Formatting cause ids
+## Reassign other drug use disorders
+# Non-opioid use disorders is a BHI-specific cause that is an aggregate of the following disorders:
+#   - cocaine use disorders
+#   - amphetamine use disorders
+#   - cannabis use disorders
+#   - other drug use disorders
+
+burden[cause_id %in% 563:566, cause_name := 'Non-opioid drug use disorders']
+
+## Aggregate measures for reassigned cause
+burden_agg <- burden[, .(val = sum(val, na.rm = T)),
+                     by = .(location_id, location_name, year_id, sex_id, age_group_name, cause_name, measure)]
+
+## Reshape long to wide by measure
+burden_wide <- dcast.data.table(burden_agg, location_id + location_name + year_id + sex_id + age_group_name + cause_name ~ measure, value.var = 'val')
+
+## Calculate YLDs per case (disability weight)
+burden_wide[, yld_per_case := yld / prevalence]
+
+# adding age group id
+burden_wide <- merge(burden_wide, age_group_id_table, by = 'age_group_name', all.x = T)
+
+## Reshape long to wide by year to make more readable
+burden_wide_years <- dcast.data.table(burden_wide, location_id + location_name + sex_id + age_group_name + age_group_id + cause_name ~ year_id, value.var = 'yld_per_case')
+
+# Saving out dt
+fwrite(burden_wide, "FILEPATH/average_disability_weights_by_loc_year_no_age_sex.csv")
+fwrite(burden_wide_years, "FILEPATH/average_disability_weights_by_loc_year_no_age_sex_wide_by_year.csv")