Modeling the impact of population aging on demand for healthcare

This project develops an approach to modeling the effects of demographic change on future demand for healthcare.

Running the code

There are 3 pipelines,

• population - handles population inputs
• activity - handles activity inputs
• results - builds and runs models using population and activity inputs

Population pipeline

read_historic_pop.r
read-in historic population estimates for 2000 to 2022
read_snpp_2018b.r
read-in 2018b sub-national population projections
read_npp_2018b.r
read-in 2018b national population projections
read_life_tables_2018b.r
read-in 2018b life tables from national population projections
read_life_tables_2020b.r
read-in 2020b life tables from national population projections
build_historic_pop.r
build full set of historic populations for app
build_snpp_2018b_custom_variants.r
create a set of x17 custom snpp variants
build_pop_90_inputs.r
create a set of variants for use in the app
build_pop_100_inputs.r
model the 90+ population for snpp variants
assemble_pop_inputs.r
assemble data files (JSON) for app

Activity pipeline

read_aae_dat.r
read-in aae data (data created by proc_aae_grps.sql)
read_apc_dat.r
read-in apc data (data created by proc_apc_grps.sql)
read_opc_dat.r
read-in opcs data (data created by proc_opc_grps.sql)
clean_aae_dat.r
clean aae data - compile lads, ctys, icbs and England
clean_apc_dat.r
clean apc data - compile lads, ctys, icbs and England
clean_opc_dat.r
clean opc data - compile lads, ctys, icbs and England
assemble_activity_inputs.r
assemble data files (JSON) for app

Results pipeline

hsa_build_gams.r
create GAMs needed for health status adjustment
hsa_review_gams.r
review GAMs
hsa_build_model.r
apply logic for health status adjustment
hsa_run_model.r
fns to run the models hsa_assemble_results.r
fns to assemble model results (single area)
assemble_results_inputs.r
assemble data files (JSON) for app

License

Distributed under the MIT License. See LICENSE for more information.