Northward range expansion of Ixodes scapularis evident over a short timescale in Ontario, Canada
Bibliographic record
Abstract
The invasion of the blacklegged tick, Ixodes scapularis into Ontario, Canada poses a significant risk to public health because it is a vector for numerous pathogens, including Borrelia burgdorferi sensu stricto, the causative agent of Lyme disease. Baseline field sampling in 2014 and 2015 detected I. scapularis and B. burgdorferi at sites across southern, eastern and central Ontario, including a hot spot in eastern Ontario. A "speed of spread" model for I. scapularis developed by Leighton and colleagues (2012) estimated that the tick's range was expanding northward at 46 km/year. In 2016, we revisited a subset of sites sampled in 2014 and 2015 to understand the changing nature of risk, and assess whether the rate of tick invasion is consistent with the speed of spread estimate. Ticks were collected via tick dragging at 17 out of 36 sites, 5 of which were new sites for I. scapularis. Samples were positive for B. burgdorferi at 8 sites. No other I. scapularis-borne pathogens were detected. Centrographic statistics revealed an increase in the dispersion of I. scapularis positive sites in eastern Ontario. Field data for each site were then compared to the model's predicted year of establishment for each census subdivision. Our findings illustrate that the range expansion of I. scapularis and the emergence of B. burgdorferi is ongoing, and provide short timescale evidence of the processes associated with I. scapularis spread. The range front appears to be moving at a rate of ~46 km/year, with colonization of the tick behind this range front occurring at a slower and heterogeneous rate. Assessment of site-level ecological factors did not provide any insight into the underlying processes that may be influencing the colonization of I. scapularis in specific areas. Ongoing field sampling is needed to monitor this dynamic process. This study highlights the current geographic risk associated with Lyme disease, which can be used to target public health interventions to the areas of greatest risk.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".