The economic and health burden of COPD in Western Europe through 2050: a scenario analysis based on two large data sources
Bibliographic record
Abstract
Rationale: Given the considerable burden of COPD, studies have estimated the current prevalence of COPD in Europe, but estimates vary widely. A study by the Global Burden of Disease (GBD) concluded the 2019 COPD prevalence across Europe to be 5.8%; however, meta-analytical data suggested a prevalence of 10.3%. We aimed to forecast the future burden of COPD in Western Europe through 2050 with a simulation model using both prevalence estimates. Methods: Using country-specific data from Western Europe (n_countries = 12), a Markov model was developed to simulate population dynamics from 2019 to 2050. Population growth and mortality were modeled across subgroups of age, sex, and smoking status. COPD costs were calibrated for these subgroups, and distributions of COPD severity grades were modeled based on age, sex, and smoking status. Direct and indirect costs associated with COPD were projected to 2050. Results: The GBD-prevalence model estimated a total cumulative direct health care cost of COPD across Western Europe of €2.2 trillion by 2050, with total cumulative indirect costs of €2.7 trillion. Based on the meta-analytical-prevalence model, we estimated that by 2050, the total cumulative direct costs of COPD across Europe would be €5.2 trillion, with total cumulative indirect costs of €6.5 trillion. The total direct and indirect burden of COPD in Europe in 2050 may range between €4.5 trillion – €12.0 trillion. Conclusions: Regardless of the COPD prevalence implemented, the economic burden of COPD is substantial and expected to grow over time. These data may help to inform efforts with advocacy and help to prioritize expenditures strategically.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".