1428. Modeling Reductions in Antibiotic Prescriptions due to Otitis Media in Canada as a Result of Pneumococcal Conjugate Vaccination
Bibliographic record
Abstract
Vaccines are an important factor in combating the growing global health issue of antimicrobial resistance. Pneumococcal conjugate vaccines (PCVs) have substantially reduced the burden of otitis media (OM) caused by S. pneumoniae, one of the largest causes of antibiotic prescriptions (Abx) in children under 5. The purpose of this study was to quantify the number of Abx avoided since the introduction of a national PCV program in Canada. We adapted a previously published forecasting model to estimate the reduction in OM cases in Canada since the introduction of PCVs in all routine provincial programs in 2005 through 2015 (the last year complete data were available). The impact of PCV on OM was modeled and compared with pre-PCV incidence to estimate net impact of the vaccine. We assumed that 90% of OM episodes were treated with an initial Abx given routine practice. All data were sourced from the published literature. Over 10 years, PCVs were estimated to avert 3.7 million cases of OM in Canada. This corresponded to an estimated reduction of 3.3 million Abx, or 0.96 Abx avoided per infant vaccinated with PCV. PCVs have had a significant public health impact on reducing the burden of disease and Abx. While most of the PCV impact on reduction of Abx is due to reduction in OM cases, additional Abx reduction from prevention of other invasive and noninvasive pneumococcal diseases is of importance. Further research is necessary to understand the additional net benefit of reducing antibiotics across the disease spectrum given that reductions in net prescribing could avert further downstream resistance by other pathogens. M. C. Breton, Pfizer inc.: Employee, Salary. R. Farkouh, Pfizer: Employee, Salary. J. Vojicic, Pfizer: Employee and Shareholder, Benefits and stock and Salary. M. Wilson, Pfizer Inc: Consultant, Consulting fee. C. McDade, Pfizer Inc.: Consultant, Consulting fee. M. Wasserman, Pfizer: Employee, Salary.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".