diff --git a/src/scripts/data_file_processing/healthsystem/consumables/generating_consumable_scenarios/generate_consumable_availability_scenarios_for_impact_analysis.py b/src/scripts/data_file_processing/healthsystem/consumables/generating_consumable_scenarios/generate_consumable_availability_scenarios_for_impact_analysis.py
index bc05f733e0..ae8f3ec405 100644
--- a/src/scripts/data_file_processing/healthsystem/consumables/generating_consumable_scenarios/generate_consumable_availability_scenarios_for_impact_analysis.py
+++ b/src/scripts/data_file_processing/healthsystem/consumables/generating_consumable_scenarios/generate_consumable_availability_scenarios_for_impact_analysis.py
@@ -32,11 +32,6 @@
 
 from tlo.methods.consumables import check_format_of_consumables_file
 
-# Set local Dropbox source
-path_to_dropbox = Path(  # <-- point to the TLO dropbox locally
-    '/Users/sm2511/Dropbox/Thanzi la Onse'
-)
-
 # define a timestamp for script outputs
 timestamp = datetime.datetime.now().strftime("_%Y_%m_%d_%H_%M")
 
@@ -55,7 +50,7 @@
 #------------------------------------------------------
 tlo_availability_df = pd.read_csv(path_for_new_resourcefiles / "ResourceFile_Consumables_availability_small.csv")
 # Drop any scenario data previously included in the resourcefile
-tlo_availability_df = tlo_availability_df[['Facility_ID', 'month', 'item_code', 'available_prop']]
+tlo_availability_df = tlo_availability_df[['Facility_ID', 'month', 'item_category', 'item_code', 'available_prop']]
 
 # 1.1.1 Attach district, facility level, program to this dataset
 #----------------------------------------------------------------
@@ -66,13 +61,6 @@
 tlo_availability_df = tlo_availability_df.merge(mfl[['District', 'Facility_Level', 'Facility_ID']],
                     on = ['Facility_ID'], how='left')
 
-# 1.1.2 Attach programs
-programs = pd.read_csv(path_for_new_resourcefiles / "ResourceFile_Consumables_availability_and_usage.csv")[['category', 'item_code', 'module_name']]
-# TODO See if programs can be extracted from a different location as ResourceFile_Consumables_availability_and_usage.csv is now deprecated in master
-programs = programs.drop_duplicates('item_code')
-# manually add category for the two consumables for which it is missing
-tlo_availability_df = tlo_availability_df.merge(programs, on = ['item_code'], how = 'left')
-
 # 1.2 Import scenario data
 #------------------------------------------------------
 scenario_availability_df = pd.read_csv(outputfilepath / "regression_analysis/predictions/predicted_consumable_availability_regression_scenarios.csv")