Estimation of the Burden of Disease and Costs of Genital Chlamydia trachomatis Infection in Canada
Bibliographic record
Abstract
BACKGROUND: Rates of Chlamydia trachomatis (CT) infection in Canada have been increasing since the mid-1990s. We sought to estimate the burden of CT in this population. METHODS: We developed an age- and sex-structured mathematical model parameterized to reproduce trends in CT prevalence between 1991 and 2009 in the Canadian population aged 10 to 39 years. Costs were identified, measured, and valued using a modified societal perspective and converted to year 2009 Canadian dollars. Cost-effectiveness of the implemented policy of enhanced screening for asymptomatic infections was estimated by comparison with model-projected trends in the absence of increased screening. Main outcome measures were current net cost and burden of illness attributable to CT infection, and incremental cost-effectiveness ratios. RESULTS: Under base case model assumptions, there was a trend of increasing detection of CT cases (due to increases in screening), despite an underlying stabilization of actual CT infections. Average estimated costs associated with CT infection over this period were $51.4 million per year. Costs of screening and treatment of asymptomatic infections as a proportion of total CT costs were estimated to have increased over time, whereas costs of long-term sequelae associated with untreated infections declined over the same period. Compared with no change in screening, enhanced screening was estimated to be highly cost-effective, with an incremental cost-effectiveness ratio of $2910 per quality-adjusted life year. CONCLUSIONS: Despite increases in screening, the economic burden of CT in Canada remains high. Further investigation of trends in chlamydia-associated complications is required to better understand the impact of screening on incidence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".