Active and Passive Surveillance and Phylogenetic Analysis of <i>Borrelia burgdorferi</i> Elucidate the Process of Lyme Disease Risk Emergence in Canada
Bibliographic record
Abstract
BACKGROUND: Northward expansion of the tick Ixodes scapularis is driving Lyme disease (LD) emergence in Canada. Information on mechanisms involved is needed to enhance surveillance and identify where LD risk is emerging. OBJECTIVES: We used passive and active surveillance and phylogeographic analysis of Borrelia burgdorferi to investigate LD risk emergence in Quebec. METHODS: In active surveillance, we collected ticks from the environment and from captured rodents. B. burgdorferi transmission was detected by serological analysis of rodents and by polymerase chain reaction assays of ticks. Spatiotemporal trends in passive surveillance data assisted interpretation of active surveillance. Multilocus sequence typing (MLST) of B. burgdorferi in ticks identified likely source locations of B. burgdorferi. RESULTS: In active surveillance, we found I. scapularis at 55% of sites, and we were more likely to find them at sites with a warmer climate. B. burgdorferi was identified at 13 I. scapularis-positive sites, but infection prevalence in ticks and animal hosts was low. Low infection prevalence in ticks submitted in passive surveillance after 2004-from the tick-positive regions identified in active surveillance-coincided with an exponential increase in tick submissions during this time. MLST analysis suggested recent introduction of B. burgdorferi from the northeastern United States. CONCLUSIONS: These data are consistent with I. scapularis ticks dispersed from the United States by migratory birds, founding populations where the climate is warmest, and then establishment of B. burgdorferi from the United States several years after I. scapularis have established. These observations provide vital information for public health to minimize the impact of LD 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".