Risk of transfusion‐transmitted <i>Babesia microti</i> in Canada
Bibliographic record
Abstract
BACKGROUND: Babesia microti has gained a foothold in Canada as tick vectors become established in broader geographic areas. B. microti infection is associated with mild or no symptoms in healthy individuals but is transfusion-transmissible and can be fatal in immunocompromised individuals. This is the first estimate of clinically significant transfusion-transmitted babesiosis (TTB) risk in Canada. STUDY DESIGN AND METHODS: The proportion of B. microti-antibody (AB)/nucleic acid amplification test (NAT)-positive whole blood donations was estimated at 5.5% of the proportion of the general population with reported Lyme Disease (also tick-borne) based on US data. Monte Carlo simulation estimated the number and proportion of infectious red cell units for three scenarios: base, localized incidence (risk in Manitoba only), and donor study informed (prevalence from donor data). The model simulated 1,029,800 donations repeated 100,000 times for each. RESULTS: In the base scenario 0.5 (0.01, 1.75), B. microti-NAT-positive donations would be expected per year, with 0.08 (0, 0.38) recipients suffering clinically significant TTB (1 every 12.5 years). In the localized incidence scenario, there were 0.21(0, 0.7) B. microti-NAT-positive donations, with 0.04 (0, 0.14) recipient infections (about 1 every 25 years). In the donor study informed scenario, there were 4.6 (0.3, 15.8) B. microti-NAT-positive donations expected, and 0.81 (0.05, 3.14) clinically significant TTB cases per year. DISCUSSION: The likelihood of clinically relevant TTB is low. Testing would have very little utility in Canada at this time. Ongoing pathogen surveillance in tick vectors is important as B. microti prevalence appears to be slowly increasing in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".