Hepatitis C Elimination in Egypt: Story of Success
Bibliographic record
Abstract
Egypt has long been overwhelmed by the hepatitis C virus (HCV) infection, and it used to be the country with the world's highest prevalence rates. The disease had been a significant public health problem, affecting millions of Egyptians and posing severe economic and social challenges. By the early 2000s, it was estimated that around 10% of the Egyptian population was infected with HCV. However, in recent years, with the availability of direct-acting antiviral therapies, the country has made enormous steps in combating this public health threat. The combination of innovative health strategies and political will enabled Egypt to establish a successful model of care for HCV management and to be the first country to eliminate hepatitis C, setting a model for the rest of the world. In 2023, Egypt became the first country to fulfill the World Health Organization's set programmatic criteria of reduction of hepatitis C incidence and mortalities to levels close to elimination of disease or achieve the "gold tier" status on the path to disease elimination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".