Detection of atypical bacteria, including <i>Mycoplasma pneumoniae</i>, British Columbia, Canada, 2013–2023
Bibliographic record
Abstract
Background: Global reports suggest heightened Mycoplasma pneumoniae (Mp) activity during the fall of 2023. However, it is unclear how testing strategy changes and preventative measures implemented during the COVID-19 pandemic influenced these conclusions. The objective of this study was to summarize the effects of implementing a new respiratory testing method (Luminex NxTAG Respiratory Pathogen Panel [RPP]) on the rate of detection of three types of atypical bacteria (AB) (Mp, Legionella pneumophila [Lp], and Chlamydophila pneumoniae [Cp]) in British Columbia (BC), as well as to summarize case detections throughout the province during and after the COVID-19 pandemic to determine if there were emerging concerns regarding Mp infections in BC as seen in other jurisdictions. Methods: We analyzed 2013–2023 laboratory testing data from the provincial lab in BC, divided into periods before syndromic testing, after syndromic testing was implemented (via xTAG RPP), during the COVID-19 pandemic, and after the pandemic. Results: Following introduction of the Luminex NxTAG RPP, detection of Mp and Cp cases increased 11-fold and 4-fold, respectively, while Lp detection was not significantly affected. Relatively few cases of Mp were recorded during the COVID-19 pandemic, although following relaxation of COVID-19 pandemic mitigation measures, Mp resurgent activity was observed that remained within expected levels. Conclusions: Detection of AB in BC increased following implementation of the Luminex NxTAG RPP, decreased during the COVID-19 pandemic, and returned to seasonal circulation after the pandemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".