An evaluation on the outcomes of the Sekolah Rakan Alam Sekitar(SERASI) programme in Sabah, Malaysia
Bibliographic record
Abstract
In order to detect the SARS-CoV-2 variants of concern (VOCs), five real-time reverse transcriptase PCR (rRT-PCR) assays were designed to target the critical discriminatory mutations responsible for the following amino acid changes in the spike protein: two Δ69-70 + N501Y + E gene triplexes (one optimized for Alpha [B.1.1.7] and one optimized for Omicron [B.1.1.529]), a K417N + 242-244 wild-type duplex, a K417T + E484K duplex, and a L452R + P681 + E484Q triplex. Depending on the assay, sensitivity was 98.97-100% for the detection of known VOC-positive samples, specificity was 97.2-100%, limit of detection was 2-116 copies/reaction, intra- and interassay variability was less than 5%, and no cross-reactivity with common respiratory pathogens was observed with any assay. A subset of rRT-PCR- positive VOC samples were further characterized by genome sequencing. A comparison of the lineage designation by the VOC rRT-PCR assays and genome sequencing for the detection of the Alpha, Beta, Gamma, Delta and Omicron variants showed clinical sensitivities of 99.97-100 %, clinical specificities of 99.6-100 %, positive predictive values of 99.8-100%, and negative predictive values of 99.98-100 %. We have implemented these rRT-PCR assays targeting discriminatory single nucleotide polymorphisms for ongoing VOC screening of SARS-CoV-2 positive samples for surveillance purposes. This has proven extremely useful in providing close to real-time molecular surveillance to monitor the emergence of Alpha, the replacement of Alpha by Delta, and the replacement of Delta by Omicron. While the design, validation and implementation of the variant specific PCR targets is an ever-evolving approach, we find the turn-around-time, high throughput and sensitivity to be a useful complementary approach for SARS-CoV-2 genome sequencing for surveillance purposes in the province of Alberta, Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".