Can we afford not to screen and treat hepatitis C virus infection in Canada?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Screening for hepatitis C virus (HCV) followed by direct-acting antiviral (DAA) treatment in individuals born between 1945 and 1964 has been shown to be both effective and cost-effective, but the question of affordability remains unresolved. We looked at long-term cost and health outcomes of HCV screening for Ontario up to 2030. Methods: We used a validated state-transition model to analyze the budget and health impact of HCV screening followed by DAA treatment in individuals born between 1945 and 1964 versus current practice. We used a payer's perspective, discounting costs at an annual rate of 1.5%. Costs, liver-related deaths, and hepatocellular carcinoma (HCC) and decompensated cirrhosis (DC) cases detected were measured over a 14-year period. Results: By 2030, the cost of implementing a HCV screening program for individuals born between 1945 and 1964 will add an additional $845 million to the Ontario health care budget. Sensitivity analyses showed that DAA costs had the largest effect on the budget, and decreasing DAA costs to $16,000 will lead to a significantly lower budget impact of $331 million. Regarding population health, a screen-and-treat strategy will prevent 1,199 cases of HCC, 1,565 cases of DC, and 1,665 liver-related deaths by 2030. Conclusions: Contrasting the budget impact of this HCV screening strategy with other recommended health services and technologies, we conclude that HCV screening should be considered affordable. If Canada is committed to meeting the targets set out by the World Health Organization, then provinces cannot afford to not expand current screening programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it