Cost-impact study of rotavirus vaccination programme in Scotland
Bibliographic record
Abstract
Aim: In July 2013, the Scottish Government introduced a rotavirus vaccination programme into the childhood immunisation schedule. The aim of this research was to estimate the cost-impact of this programme.Methods: Data for rotavirus-related resource use were identified including laboratory reports, hospitalisations, attendances at accident and emergency departments (A&E), general practice consultations (GP), calls to the National Health Service telephone helpline (NHS24) and prescriptions for common rehydration treatments. We used an interrupted time series analysis approach to assess the impact on resource utilisation in all categories. Appropriate costs were added to the models and predicted pre-and post-vaccination mean annual costs were estimated. The cost of the vaccination programme was estimated using costs from the literature.Results: The vaccination programme was associated with a reduction in utilisation in all measured healthcare resource categories. These reductions were all statistically significant (at the 95% level) with p-values less than 0.001. Reductions ranged from 18% in calls to NHS24 to 73% in positive laboratory reports. The vaccination programme was associated with a reduction in annual healthcare resource costs of 38% (£595,000 per 100,000 infants < 5 years old) in our measured categories (including £495,000 from a reduction in hospital stays). The annual overall cost-impact of the rotavirus vaccination programme (the cost of delivering the programme minus the reduction in resource costs) was estimated at approximately £435,000 per 100,000 infants < 5 years old.Conclusion: The rotavirus vaccination programme was associated with a reduction in all measured categories of rotavirus-related resource use by infants < 5 years old.
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.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".