Enhanced surveillance for measles in low-incidence territories of the Russian Federation: defining a rate for suspected case investigation
Bibliographic record
Abstract
The rate of case investigation for measles-like illness (MLI) is an important indicator for the quality of measles surveillance in countries targeting measles elimination. However, a benchmark rate is still being discussed. We assessed different rates of investigation in 11 territories of the Russian Federation with low reported measles incidence during the previous 4-7 years. Each territory maintained their existing surveillance activities and also undertook additional surveillance activities for MLI over a 3-year period. The annual routine rate of investigation varied from 0·06 to 1·8/100,000 population; the overall rate of investigation, including enhanced surveillance, varied from 1·4 to 7·2/100,000. Forty-nine (30·8%) of 159 measles cases detected were identified through enhanced surveillance. Based on the results of this study, the Russian Federation concluded that a rate of routine investigation of 2/100,000 provided the best balance between available resources and sensitivity for detection of measles cases.
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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 | 0.005 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".