Prevalence of Borrelia burgdorferi, Anaplasma spp., Ehrlichia spp. and Dirofilaria immitis in Canadian dogs, 2008 to 2015: a repeat cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Vector-borne pathogens are emerging concerns in multiple regions of Canada. Determining regional prevalence of canine vector-borne pathogens and documenting change will improve clinician awareness, enable targeted prevention, enhance diagnosis and ideally reduce the risk of disease. Study objectives were to: (i) estimate the prevalence of positive canine vector-borne test results from samples submitted in Canada; (ii) assess change in prevalence over time, from baseline (2008) to 2015; and (iii) estimate the prevalence of pathogen co-infections. METHODS: This repeat cross-sectional study evaluated 753,468 test results for D. immitis antigen and B. burgdorferi, Ehrlichia canis/ewingii/muris serology, and 753,208 test results for Anaplasma phagocytophilum/platys serology using the SNAP® 4Dx®Test and SNAP 4Dx® Plus Test. RESULTS: Based on all submitted samples from Canada (2008-2015), the period seroprevalence of B. burgdorferi, Ehrlichia spp., Anaplasma spp. and D. immitis antigen were 2.0%, 0.5%, 0.4% and 0.2%, respectively. Over the 7 years (2008 compared to 2015) we observed a significant increase in seroprevalence for B. burgdorferi (144.4%) and Ehrlichia spp. (150%). Co-infections (positive for two or more pathogens on a single 4 pathogen test kit) were estimated at 5.4% (1162/21,612) of total positive tests. CONCLUSIONS: The temporal rise and geographical differences in prevalence detected for these pathogens (notably B. burgdorferi) are consistent with anecdotal information on canine illness related to tick-borne pathogen exposure in multiple regions of Canada, particularly canine Lyme disease.
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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 | 0.002 | 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 | 0.001 |
| 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".