The Ecology and Epidemiology of the Blacklegged Tick, Ixodes scapularis, and the Risk of Lyme Disease in Ontario, Canada
Bibliographic record
Abstract
This thesis is an investigation of the ecology and epidemiology of Ixodes scapularis and the risk of Lyme disease in Ontario, Canada. Over the past two decades, there has been rapid range expansion of I. scapularis northward into Canada. This tick is a vector for numerous pathogens of human and animal health significance, including Borrelia burgdorferi sensu stricto, the causative agent of Lyme disease in North America. In 2014 and 2015, tick dragging was conducted at 154 sites across southern, eastern and central Ontario. Ecological data were also collected at each site. Ixodes scapularis were detected at 29 of 154 sites, with a “hot spot” for I. scapularis identified in eastern Ontario. Nine sites had B. burgdorferi-positive ticks. The presence of I. scapularis at a site was positively associated with cumulative degree days above zero and negatively associated with westward longitude, based on mixed multivariable logistic regression. The relative abundance of shrubs, the density of the understory and the interaction of these two variables were also significant. Follow-up field sampling for I. scapularis was conducted at 36 sites in 2016 to assess the spatial spread of the tick. Ixodes scapularis was detected at five new sites in eastern Ontario. These findings were consistent with the estimated speed of range front expansion by Leighton et al. (2012). Colonization of I. scapularis at sites behind this range front is occurring at a slower and heterogeneous rate. Data from field sampling and previous surveillance of I. scapularis were used to create an ecological risk indicator to assist public health professionals with risk assessment for reproducing populations of I. scapularis. This thesis provides valuable knowledge on the distribution, spread and ecology of an emerging vector and pathogen, and can be used to target public health interventions.
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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 | 0.003 | 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".