Coverage of Haemophilus influenzae Type b Conjugate Vaccine for Children in Mainland China
Bibliographic record
Abstract
BACKGROUND: Use of Haemophilus influenzae type b conjugate vaccine is effective in reducing the disease burden, but its coverage in China is unclear. The aim of this meta-analysis is to assess the coverage of Hib conjugate vaccines in children in Mainland China. METHODS: We systematically searched Pubmed, Web of Science, Medline, CNKI and Wanfang to identify studies assessing the coverage of Hib vaccine in Chinese children. Random-effects models were used to obtain pooled estimates for Hib vaccine coverage and analyzed heterogeneity with meta-regression and subgroup analyses. RESULTS: Thirty-three studies that included 7,227,480 subjects in 12 provinces met our inclusion criteria. The pooled overall coverage of Hib conjugate vaccine was 54.9% [95% confidence interval (CI): 52.9-57.0]. The pooled coverage for the nonlocal population (54.3%; 95% CI: 52.4-56.3) was lower than that for the local residents (62.0%; 95% CI: 58.4-65.6). The region-pooled coverage was higher in the east of China (59.7%; 95% CI: 57.3-62.1) than in the central and west parts of the country (48.5%; 95% CI: 40.6-56.4). Overall, 26.7% (95% CI: 20.1-33.2) had 1 dose only, 14.8% (95% CI: 10.0-19.6%) had 2 doses, 13.5% (95% CI: 9.1-17.8) had 3 doses and 14.3% (95% CI: 9.7-18.9) had 4 doses. CONCLUSIONS: We found a low coverage of Hib conjugate vaccine, particularly for the nonlocal children and those living in the central and west parts of China. Including Hib vaccine into the national immunization program is recommended to reduce disparities in vaccination coverage.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".