National Responses to HIV Versus HCV-Infection from Virally Contaminated Blood Products among Persons with Hemophilia (PWH): More Different Than Alike.
Bibliographic record
Abstract
Abstract Background: 95% of HIV- and HCV-infections among PWHs occurred with use of contaminated blood products prior to 1985. Overall, 20% to 90% of PWHs in developed countries have HIV- and/or HCV-infection. We compared country-specific public health approaches, judicial activities, and compensation for these viral infections. Methods: Reports from hemophilia organizations, national ministries of health, published articles, and the World Federation of Hemophilia were reviewed. Results: Except for the United States, the number of PWHs who developed HCV-infection from contaminated blood products was 1.5 to 3-fold as great as for HIV-infection- as a result of delayed use of heat-treated blood products, importation in late 1984 of HCV-infected non-heat treated blood products from the United States, and failure to use surrogate laboratory marker hepatitis screening tests. Compensation funds for HIV-infected PWHs were established in Japan ($521,000 at Dx); France ($305,000 at Dx; $102,000 for AIDS); the United States ($115,000 at Dx); Ireland ($106,000 at Dx); the United Kingdom ($55,000 at Dx); Australia ($48,000 at Dx); Canada ($13,000 at Dx/$18,000/yr); Germany ($12,000/yr for HIV; $24,000/yr for AIDS); and Italy ($6,000/yr; $82,000 at death). Compensation has also been provided to HCV-infected PWHs in Ireland ($266,000 at Dx); Canada ($251,000 at Dx); the United Kingdom ($33,000 at Dx; $42,000 if w/liver damage); and Italy ($10,000/yr; $37,000 at death). Conclusions: In most developed countries, despite a greater number of HCV-versus HIV-infected PWHs, markedly less attention has been paid to HCV-infected PWHs. All countries should review HCV-related blood safety decisions made in the 1980s and consider providing compensation to HCV-infected PWHs. A comparison of national responses to HIV and HCV infections from blood products Country -PWH (thousands) % PWH with HIV:HCV Man-dated HIV ELISA (date) Man-dated heat Rx factor (date) Anti-HBc marker screening (date) Nat’l Funds for HIV/HCV among PWHs (year) Nat’l Panels for HIV/HCV decisions (year) USA-20 50%:30% Mar 85 Oct 84 Oct 84 96/none 95/none Italy- 8.7 23%:55% Mar 85 Jul 85 None 92/98 92/05 GDR- 6 47%:90% Oct 85 Oct 85 None 95/none 94/none UK-6 28%:80% Oct 85 Jun 85 None 88/03 87/05 France-4 50%:90% Aug 85 Oct 85 None 89/none 91/none Japan-3.4 60%:90% Nov 86 Jun 86 None 88/none 96/none Canada-2 40%:88% Nov 85 Jul 85 None 89/98 97/none Australia-1.5 31%:90% May 85 Jan 85 None 89/none 88/none Ireland-0.3 36%:76% Oct 85 Feb 85 None 91/97 91/97
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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 | 0.003 |
| 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 | 0.001 |
| 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".