Lyme Disease Emergence after Invasion of the Blacklegged Tick,<i>Ixodes scapularis</i>, Ontario, Canada, 2010–2016
Bibliographic record
Abstract
Analysis of surveillance data for 2010-2016 in eastern Ontario, Canada, demonstrates the rapid northward spread of Ixodes scapularis ticks and Borrelia burgdorferi, followed by increasing human Lyme disease incidence.Most spread occurred during 2011-2013.Continued monitoring is essential to identify emerging risk areas in this region.L yme disease (LD) is the most reported vectorborne dis- ease in North America, where it is caused by Borrelia burgdorferi sensu stricto and principally transmitted by the blacklegged tick (Ixodes scapularis) (1).With northward expansion of I. scapularis tick populations from endemic areas in the United States, LD is rapidly emerging in parts of central and eastern Canada (2-4).Although several studies have mapped blacklegged tick populations across Canada and developed models to predict future spread of ticks and LD risk (2,3), little is known about the extent of human LD in relation to tick vector distributions at a fine geographic scale.We examined spatiotemporal trends in the occurrence and expansion of I. scapularis ticks, B. burgdorferi-infected ticks, and human LD cases over a 7-year period to elucidate the process of LD emergence in eastern Ontario, Canada. The StudyOur study included 3 public health units in eastern Ontario, Canada: Kingston, Frontenac, and Lennox and Addington (KFL); Leeds, Grenville, and Lanark (LGL); and Ottawa.This region spans from the St. Lawrence River in the south to the Ottawa River in the north, and has several major population centers, including Kingston (2016 population 123,798) and Ottawa (2016 population 934,243) (5).The region is largely characterized by mixed deciduous forest and agricultural land use.We used data from the Integrated Public Health Information System database to identify human LD cases
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".