An estimation of the worldwide economic and health burden of visual impairment
Bibliographic record
Abstract
This study aims to provide a rigorous estimate of the worldwide costs of visual impairment (VI), and the associated health burden. The study used a prevalence-based model. Prevalence rates for mild VI (visual acuity (VA) worse than 6/12 but not worse than 6/18), moderate VI (VA worse than 6/18 but not worse than 6/60) and blindness (VA worse than 6/60) were applied to population forecasts for each World Health Organisation (WHO) subregion. The limited available country cost data were extrapolated between subregions using economic and population health indicators. Age and gender subgroup population numbers were derived from United Nations' data. Costs and the health burden of VI were estimated for each world subregion using published disease prevalence rates, health care expenditures and other economic data. The study includes direct health care costs, indirect costs and the health burden of VI. The total cost of VI globally was estimated at $3 trillion in 2010, of which $2.3 trillion was direct health costs. This burden is projected to increase by approximately 20% by 2020. VI is associated with a considerable disease burden. Unless steps are taken to reduce prevalence through prevention and treatment, this burden will increase alongside global population growth.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".