Spatial distribution of seroprevalence for<i>Anaplasma phagocytophilum</i>,<i>Borrelia burgdorferi</i>,<i>Ehrlichia canis</i>, and<i>Dirofilaria immitis</i>in dogs in Washington, Oregon, and California
Bibliographic record
Abstract
BACKGROUND: In the US little spatially defined information regarding exposure to most vector-borne pathogens in dogs is available for the states of California (CA), Oregon (OR), and Washington (WA). OBJECTIVES: The purpose of the present study was to evaluate the spatial distribution of seroprevalence for 4 vector-borne pathogens, Anaplasma phagocytophilum, Borrelia burgdorferi, Ehrlichia canis, and Dirofilaria immitis, across the 3 western coastal states of the contiguous United States that extend from the northern Mexican to the southern Canadian border. METHODS: A convenience sample, targeting blood from 20 pet dogs per county across CA, OR, and WA, was evaluated using a canine point-of-care ELISA kit. Geographic coordinates of home zip code were displayed using a geographic information system. A total of 2431 dogs from CA, OR, and WA were tested. RESULTS: The overall seroprevalence was highest for A. phagocytophilum (2.4%), followed by B. burgdorferi (1.2%), and E. canis (0.7%). The prevalence of infection with D. immitis was 0.7%. At the individual dog level, there was a significant association between seropositivity to B. burgdorferi and A. phagocytophilum (odds ratio=18.7, 95% confidence interval=6.8-47.1). For most positive results, prevalence tended to decrease with increasing latitude; thus, the highest rates of seropositivity occurred in CA, followed by OR, and then WA; one exception was seropositivity for B. burgdorferi, which was higher in WA (0.38%) than in OR (0.15%), but considerably lower than in CA (2.00%). In WA, dogs that tested positive for A. phagocytophilum, E. canis, and B. burgdorferi were in the southern Puget Sound area. For D. immitis, none of the dogs in WA was positive. CONCLUSIONS: Seropositivity for vector-borne pathogens is broadly but patchily distributed in dogs in CA, OR, and WA.
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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 | 0.001 |
| 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".