The epidemiologic burden of hepatitis C virus infection in Latin America
Bibliographic record
Abstract
Chronic infection with hepatitis C virus (HCV) is a major and growing public health concern worldwide, including in Latin America. With more efficacious therapies becoming available, decision-makers will require accurate estimates of disease prevalence to assess the potential impact of new treatments. However, few estimates of the epidemiologic burden, either overall or by country, are available for Latin America; and the potential impact of currently-available treatments on the epidemiologic burden of HCV in Latin America has not been assessed. To address this, we systematically reviewed twenty-five articles presenting population-based estimates of HCV prevalence from general population or blood donor samples, and supplemen- ted those with publically-available data, to estimate the total number of persons infected with HCV in Latin America at 7.8 million (2010). Of these, over 4.6 million would be expected to have genotype 1 chronic HCV, based on published data on the risk of progression to chronic disease and the HCV genotype distribution of Latin America. Finally, we calculated that between 1.6 and 2.3 million persons with genotype 1 chronic HCV would potentially benefit from current treatments, based on published estimates of genotype-specific treatment responsiveness. In conclusion, these estimates demonstrate the substantial present epidemiologic burden of HCV, and quantify the impending societal and clinical burden from untreated HCV in Latin America.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".