Two Birds With One Stone: Estimating Population Vaccination Coverage From a Test-negative Vaccine Effectiveness Case-control Study
Bibliographic record
Abstract
Vaccination program evaluation includes assessment of vaccine uptake and direct vaccine effectiveness (VE). Often examined separately, we propose a design to estimate rotavirus vaccination coverage using controls from a rotavirus VE test-negative case-control study and to examine coverage following implementation of the Quebec, Canada, rotavirus vaccination program. We present our assumptions for using these data as a proxy for coverage in the general population, explore effects of diagnostic accuracy on coverage estimates via simulations, and validate estimates with an external source. We found 79.0% (95% confidence interval, 74.3%, 83.0%) ≥2-dose rotavirus coverage among participants eligible for publicly funded vaccination. No differences were detected between study and external coverage estimates. Simulations revealed minimal bias in estimates with high diagnostic sensitivity and specificity. We conclude that controls from a VE case-control study may be a valuable resource of coverage information when reasonable assumptions can be made for estimate generalizability; high rotavirus coverage demonstrates success of the Quebec program.
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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 | 0.092 | 0.273 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".