The effect of fluralaner treatment of small mammals on the endemic cycle of <i>Borrelia burgdorferi</i> in a natural environment
Bibliographic record
Abstract
Among approaches aimed at reducing Lyme disease risk in the environment, those targeting reservoirs of Borrelia burgdorferi Johnson are promising because they have the potential to reduce both the density of questing Ixodes scapularis Say (Acari: Ixodidea) ticks and the prevalence of B. burgdorferi in the tick population. In this 4-yr field study, we treated a population of wild small mammals with 2 densities of fluralaner baits and investigated the effect of the treatment on 3 parameters of the endemic cycle of B. burgdorferi: (i) the prevalence of infected Peromyscus mice (PIM), (ii) the density of questing nymphs (DON), and (iii) the prevalence of infected questing nymphs (NIP). We demonstrated that fluralaner baiting is effective at reducing tick infestation of Peromyscus mice, the main reservoir of B. burgdorferi in central and northeastern North America, in the laboratory and the field. Results from this study showed a significant decrease in B. burgdorferi infection in mice (odds ratio: 0.37 [CI95: 0.17 to 0.83]). A reduction in the DON between 45.4% [CI95: 22.4 to 61.6] and 62.7% [CI95: 45.9 to 74.2] occurred in treated area when compared with control areas. No significant effect was reported on the NIP. These results confirm the hypothesis that fluralaner baits have an effect on B. burgdorferi endemic cycle, with the potential to reduce the density of B. burgdorferi-infected ticks in the environment. Further studies performed in various habitats and public health intervention contexts are needed to refine and operationalize this approach for reducing Lyme disease risk in the environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".