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Record W4401511215 · doi:10.3390/pathogens13080681

Hepatitis C Elimination in Egypt: Story of Success

2024· review· en· W4401511215 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePathogens · 2024
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPublic healthEnvironmental healthHepatitis CMedicineHepatitis C virusPopulationDiseaseIncidence (geometry)Developing countryEconomic growthVirologyVirusEconomicsNursing

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.088
GPT teacher head0.428
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it