Assessment of the Hepatitis C Surveillance System in Henan, China: 2014~2016
Bibliographic record
Abstract
OBJECTIVES: To access the Hepatitis C (HepC) surveillance program in Henan, China, 2014~2016. METHODS: A total of 8,448 HepC-relevant cases were reviewed and this data was then inquired against the 6,147 archived HepC reports during the same time period. The performance of the HepC surveillance program was evaluated using parameters including Timely Reporting Rate (TRR), pairs of Report Sensitivity (RS)/Underreporting Rate (UR), and False Report Rate (FRR)/Predictive Value Positive (PVP). Longitudinal comparisons of report quality over the three examined years were conducted to determine the temporal trend of HepC surveillance accountability. RESULTS: All HepC reports were submitted within 24 hours post diagnosis, and TRR rates for all examined years remained at 100%. The RS rates significantly improved overtime for clinically diagnosed HepC cases (CDHC) (2014:60.32%, 2015:68.13%, and 2016:82.83%), whereas the RS for confirmed HepC cases (CHC) remained relatively constant (80.77%, 88.64%, and 85.82%). The FRR rates for CDHC and CHC in 2015~2016 were both approximately 30% but at 23.61% and 51.85%, respectively, in 2014. CONCLUSIONS: The HepC surveillance system in Henan remains effective and consistent improvement in report accountability was observed over time. However, some issues concerning especially RS and PVP remained to be addressed for ensuring data accountsbility.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".