Economic evaluation of the benefits of reducing acute cardiorespiratory morbidity associated with air pollution
Bibliographic record
Abstract
BACKGROUND: Few assessments of the costs and benefits of reducing acute cardiorespiratory morbidity related to air pollution have employed a comprehensive, explicit approach to capturing the full societal value of reduced morbidity. METHODS: We used empirical data on the duration and severity of episodes of cardiorespiratory disease as inputs to complementary models of cost of treatment, lost productivity, and willingness to pay to avoid acute cardiorespiratory morbidity outcomes linked to air pollution in epidemiological studies. A Monte Carlo estimation procedure was utilized to propagate uncertainty in key inputs and model parameters. RESULTS: Valuation estimates ranged from 13 dollars (1997, Canadian) (95% confidence interval, 0-28 dollars) for avoidance of an acute respiratory symptom day to 5,200 dollars (4,000 dollars-6,400 dollars) for avoidance of a cardiac hospital admission. Cost of treatment accounted for the majority of the overall value of cardiac and respiratory hospital admissions as well as cardiac emergency department visits, while lost productivity generally represented a small proportion of overall value. Valuation estimates for days of restricted activity, asthma symptoms and acute respiratory symptoms were sensitive to alternative assumptions about level of activity restriction. As an example of the application of these values, we estimated that the observed decrease in particulate sulfate concentrations in Toronto between 1984 and 1999 resulted in annual benefits of 1.4 million dollars (95% confidence interval 0.91-1.8 million dollars) in relation to reduced emergency department visits and hospital admissions for cardiorespiratory disease. CONCLUSION: Our approach to estimating the value of avoiding a range of acute morbidity effects of air pollution addresses a number of limitations of the current literature, and is applicable to future assessments of the benefits of improving air quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".