Rodent-targeted fluralaner baiting reduces the density of Borrelia burgdorferi-infected questing Ixodes scapularis ticks in a peri-urban setting in southern Canada
Bibliographic record
Abstract
Lyme disease (LD) is a threat to public health in southern regions of Canada. In response, we used a One Health approach to design an integrated intervention in a high-incidence LD community in southern Québec aiming to increase preventive behaviours in the population and reduce the density of Borrelia burgdorferi-infected Ixodes scapularis ticks in the environment. The environmental component involved distributing fluralaner baits to rodents around residential properties and public trails from 2019 to 2023. Effectiveness was measured by changes in the density of questing nymphs (DON) and the prevalence of B. burgdorferi-infected nymphs (NIP). Treated areas were compared to areas located between 0 and 250 m from treatment locations and to untreated areas located >250 m away. The DON was reduced by 39 % (95 % confidence interval [95 % CI] = 1 - 62 %) in treated areas when compared to untreated areas in 2021 and 2022. Over this same period, in areas between 0 and 250 m, the DON was lower when closer to bait stations (P = 0.001). The treatment significantly reduced the NIP in treated area in 2020 (Odds ratio [OR] = 0.87 [95 % CI 0.08 - 0.98]), 2021 (OR = 0.85 [95 % CI 0.26 - 0.97], and 2022 (OR = 0.88 [95 % CI 0.12 - 0.98]), and in areas between 0 and 250 m in 2020 (OR = 0.87 [0.08 - 0.98]) and 2021 (OR = 0.84 [95 % CI 0.25 - 0.97]). This study confirms the potential of rodent-targeted fluralaner baiting for reducing the density of infected questing nymphs in peri‑urban environments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".