Multiple anthelmintic drug resistance in the canine hookworm Ancylostoma caninum: AAVP position paper and research needs
Bibliographic record
Abstract
Cases of infection with the canine hookworm Ancylostoma caninum that are resistant to all anthelmintic classes registered in the United States of America (USA) for control of this parasite in dogs were first reported in 2019. Termed Multiple Anthelmintic Drug Resistance (MADR), cases have subsequently been reported in pet dogs across the USA. Recent studies using molecular tests that detect mutations known to cause resistance to benzimidazole anthelmintics have revealed an alarming frequency of this trait in pet dogs throughout the USA, with some reports also from Canada. Since the initial reports in the USA that dog hookworms resistant to benzimidazoles were also resistant to pyrantel and macrocyclic lactones, this genetic evidence suggests that MADR worms are now widely present in the USA. The trait originally evolved on greyhound farms and kennels. However, the problem is no longer limited to greyhounds; recent studies have demonstrated that essentially any breed, age, size and sex of dogs throughout the USA can get infected with drug-resistant and possibly MADR isolates of A. caninum. In this perspective, we review current knowledge of the origin of MADR canine hookworms, tests available to diagnose MADR hookworms, and therapeutic options for treating dogs with such cases. Additionally, we propose research priorities for developing a deeper understanding of the biology of MADR worms, as well as for developing new therapeutic options to address the problem. Adding to the urgency of the situation, A. caninum is a zoonotic parasite, capable of causing disease in humans.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".