Granulocytic anaplasmosis and Lyme borreliosis exposure of horses in Canada
Bibliographic record
Abstract
A set of studies was designed in order to better understand the exposure of horses in Canada to Ixodes-borne diseases, namely equine granulocytic anaplasmosis (EGA, caused by Anaplasma phagocytophilum) and Lyme borreliosis (LB, caused by Borrelia burgdorferi). In the first study, equine serum samples submitted to veterinary diagnostic laboratories in SK, MB and ON were tested for antibodies against A. phagocytophilum and B. burgdorferi, using the point-of-care SNAP® 4Dx® ELISA. Horses seropositive to EGA were found in SK and MB and horses seropositive to LB were found in SK, MB and ON. Overall seroprevalence according to the SNAP® 4Dx® ELISA was 0.53% for EGA and 1.6% for LB. Samples that tested positive for antibodies against A. phagocytophilum (n=2) and B. burgdorferi (n=6) by SNAP® 4Dx® ELISA and 2 randomly selected subsets of samples that tested negative (n=92 each) were then re-tested using currently recommended serologic methods, and test results were compared. A lack of agreement was found between the SNAP® 4Dx® ELISA and indirect immunofluorescent assay (IFA) for EGA (McNemar test p = 0.000001). Agreement of the SNAP® 4Dx® ELISA and ELISA confirmed with Western Blot (WB) for LB was only fair (Kappa 0.23). Due to the lack of agreement between serologic tests for EGA and LB in the first study, another study to further evaluate the agreement among available serologic tests was conducted. A set of 50 convenience serum samples submitted to the veterinary diagnostic laboratory in SK was tested by SNAP® 4Dx® Plus ELISA for antibodies against A. phagocytophilum and B. burgdorferi. Samples were also tested by IFA for antibodies against A. phagocytophilum in two referral laboratories, and by IFA, ELISA confirmed with WB and Equine Lyme multiplex assay for antibodies against B. burgdorferi in three referral laboratories. Again, test results varied between the different tests. For EGA, all 3 pair-wise test comparisons lacked agreement. For LB, agreement between tests ranged from poor to fair. Differences in test methodology and antigens used, cut-off settings between the laboratories and false positive or false negative results are likely the cause for the different assessment of the same sample as seropositive or seronegative. In the third study, the goal was to describe potential risk factors for exposure of horses in Canada to EGA and LB. Management factors in horses that tested seropositive or seronegative for EGA or LB, respectively, in the previous studies were evaluated. Horse owners were surveyed with regard to their horses’ signalment, timing of pasture housing, and province of residence, travel history, tick infestation history, history of Lyme vaccination and history of previously diagnosed tick-borne disease. Response rate (11.5%) and the number of seropositive horses available for evaluation were low, which precluded statistical analysis. The majority of seropositive horses resided in SK, was pastured in the fall, did not have a recent travel history and had not had visible tick infestation. These observations supported exposure of horses to tick-borne diseases within Canada. Potential risk factors require further investigation. As information about tick infestation in horses is scarce in general, a passive surveillance study of horse ticks in SK was conducted in 2012 and 2013. A total of 833 ticks from over 86 horses were received. All ticks were Dermacentor species, i.e. D. albipictus, D. andersoni and D. variabilis. D. albipictus ticks were mostly received in February and March, D. andersoni mainly in April and June and D. variabilis mostly in May and June. Geographic distribution of the species in SK was similar to that previously reported based on active and passive surveillance. No Ixodes species were received.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".