Global Patterns and Trends in Total Burden of Hepatitis B from 1990 to 2019 and Predictions to 2030
Why this work is in the frame
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Bibliographic record
Abstract
Background and Aims: Despite widespread vaccination against hepatitis B and availability of antiviral drugs, hepatitis B remained a major global public health problem. Therefore, an improved understanding of the burden of hepatitis B was required to help design strategies for global intervention. Methods: Data on hepatitis B was collected by the Global Burden of Disease (GBD) 2019 database from 1990 to 2019. Age-standardized incidence rates (ASIR), mortality rates (ASMR) and disability-adjusted life year rates (ASDR) for hepatitis B were extracted from GBD 2019 and stratified by age, level of regionals and country. Estimated annual percentage changes (EAPC) of ASIR, ASMR and ASDR were calculated to quantify the temporal trends in hepatitis B. Results: Globally, ASIR showed a continuous downward trend, from 1552.2 in 1990 to 1010.0 per 100,000 persons in 2019, with an annual decrease of 1.52% (95% CI -1.66--1.38). ASMR showed a persistent decline, declining by nearly half in 2019 compared to 1990 (6.7 vs 12.4 per 100,000 persons), with an annual decrease of 2.55% (95% CI -2.74--2.35). ASDR showed a continuing downward trend, and the EAPC was -2.55% (95% CI -2.74--2.35). This decreasing pattern was heterogeneous across regions and countries. Hepatitis B related deaths increased significantly in high socio-demographic index countries such as UK, USA, and Canada. The ARIMA model estimates a 36.14% and 6.00% decrease in ASIR and ASMR, respectively, by 2030 compared to 2015. Conclusion: Global hepatitis B morbidity and mortality rates decreased significantly from 1990 to 2019, but with a high degree of heterogeneity among regions and countries. It was still far from achieving the WHO goal of elimination of viral hepatitis by 2030, especially mortality rate.
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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 | 0.006 |
| 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 | 0.001 |
| 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 it