Factors associated with uptake of Haemophilus influenzae type b vaccination in Shanghai, China
Bibliographic record
Abstract
BACKGROUND: Haemophilus influenzae type b (Hib) vaccine is effective in reducing the burden of Hib related diseases, but little is known about factors influencing the uptake of Hib vaccine. This study aimed to assess the uptake of Hib vaccination and its associated factors in Shanghai City, China. METHODS: We used data from a retrospective cohort of 183,246 children born in 2012-2016 obtained from the Shanghai Immunization Program Information System, which provided information on the uptake of Hib vaccination. We conducted a cross-sectional study of 451 children to collect information on demographic and other factors that might be associated with Hib vaccination. RESULTS: In the retrospective cohort study, the proportions of Hib dose-1 coverage, vaccination completion and timeliness were 67.7, 52.2 and 29.4%, respectively. These measures were better among local children and increased with birth year, while there were regional differences. Hib vaccine uptake was significantly associated with maternal occupation (non-health vs health workers, OR = 2.33, 95% CI: 1.32-4.13, P = 0.004) and caregivers' awareness of Hib (yes vs no, OR = 1.75, 95% CI: 1.12-2.74, P = 0.013). CONCLUSIONS: We found low levels of coverage of dose-1 Hib vaccine, timeliness and completion, suggesting inadequate protection against Hib disease for children in Shanghai. Non-local children and those of health workers should be targeted for interventions. The inclusion of Hib vaccine into the national immunization program could help improve the uptake of Hib vaccines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".