Worldwide prevalence, genotype distribution and management of hepatitis C
Bibliographic record
Abstract
Hepatitis C virus (HCV) is one of the leading causes of chronic liver disease, cirrhosis, and hepatocellular carcinoma, resulting in major global public health concerns. The HCV infection is unevenly distributed worldwide, with variations in prevalence across and within countries. The studies on molecular epidemiology conducted in several countries provide an essential supplement for a comprehensive knowledge of HCV epidemiology, genotypes, and subtypes, along with providing information on the impact of current and earlier migratory flows. HCV is phylogenetically classified into 8 major genotypes and 57 subtypes. HCV genotype and subtype distribution differ according to geographic origin and transmission risk category. Unless people with HCV infection are detected and treated appropriately, the number of deaths due to the disease will continue to increase. In 2015, 1.75 million new viral infections were mostly due to unsafe healthcare procedures and drug use injections. In the same year, access to direct-acting antivirals was challenging and varied in developing and developed countries, affecting HCV cure rates based on their availability. The World Health Assembly, in 2016, approved a global strategy to achieve the elimination of the HCV public health threat by 2030 (by reducing new infections by 90% and deaths by 65%). Globally, countries are implementing policies and measures to eliminate HCV risk based on their distribution of genotypes and prevalence.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".