Results from the WHO external quality assessment for the respiratory syncytial virus pilot, 2016‐17
Bibliographic record
Abstract
BACKGROUND: External quality assessments (EQAs) for the molecular detection of respiratory syncytial virus (RSV) are necessary to ensure the provision of reliable and accurate results. One of the objectives of the pilot of the World Health Organization (WHO) Global RSV Surveillance, 2016-2017, was to evaluate and standardize RSV molecular tests used by participating countries. This paper describes the first WHO RSV EQA for the molecular detection of RSV. METHODS: The WHO implemented the pilot of Global RSV Surveillance based on the WHO Global Influenza Surveillance and Response System (GISRS) from 2016 to 2018 in 14 countries. To ensure standardization of tests, 13 participating laboratories were required to complete a 12 panel RSV EQA prepared and distributed by the Centers for Disease Control and Prevention (CDC), USA. The 14th laboratory joined the pilot late and participated in a separate EQA. Laboratories evaluated a RSV rRT-PCR assay developed by CDC and compared where applicable, other Laboratory Developed Tests (LDTs) or commercial assays already in use at their laboratories. RESULTS: Laboratories performed well using the CDC RSV rRT-PCR in comparison with LDTs and commercial assays. Using the CDC assay, 11 of 13 laboratories reported correct results. Two laboratories each reported one false-positive finding. Of the laboratories using LDTs or commercial assays, results as assessed by Ct values were 100% correct for 1/5 (20%). With corrective actions, all laboratories achieved satisfactory outputs. CONCLUSIONS: These findings indicate that reliable results can be expected from this pilot. Continued participation in EQAs for the molecular detection of RSV is recommended.
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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 | 0.082 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".