1 Estimating costs of sleep apnea

LAST UPDATE: 2023-01-16 13:03:20

THIS PROJECT ESTIMATES SLEEP APNEA COSTS IN EUROPE. DATA IS PUBLICLY AVAILABLE AT http://ghdx.healthdata.org/ BY CC BY-NC-ND 4.0 LICENCE. RESULTS CAN BE REPLICATED BY THIS GUIDE.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 965417.

We are interested sleep apnea costs in Europe between age group of 15-74 years old. Data is collected from the year 2019. Following countries are included to the estimation:

##  [1] "Albania"                "Armenia"                "Austria"                "Azerbaijan"             "Belarus"               
##  [6] "Belgium"                "Bosnia and Herzegovina" "Bulgaria"               "Croatia"                "Cyprus"                
## [11] "Czechia"                "Denmark"                "Estonia"                "Finland"                "France"                
## [16] "Georgia"                "Germany"                "Greece"                 "Hungary"                "Iceland"               
## [21] "Ireland"                "Italy"                  "Kazakhstan"             "Latvia"                 "Lithuania"             
## [26] "Luxembourg"             "Malta"                  "Republic of Moldova"    "Montenegro"             "Netherlands"           
## [31] "North Macedonia"        "Norway"                 "Poland"                 "Portugal"               "Romania"               
## [36] "Russian Federation"     "Serbia"                 "Slovakia"               "Slovenia"               "Spain"                 
## [41] "Sweden"                 "Switzerland"            "Turkey"                 "Ukraine"                "United Kingdom"
# plot_europe_cost.png

Sleep apnea cost can be estimated by top-down calculation method presented in Armeni et al. (2019) Cost-of-illness study of Obstructive Sleep Apnea Syndrome (OSAS) in Italy. This project utilizes estimation method with other open data science methods for 42 countries. Guide follows step-by-step data processing by R and packages such as duckdb, tidyverse, vroom and dplyr.