Ectoparasites of brown rats (Rattus norvegicus) in Grenada, West Indies
Bibliographic record
Abstract
Background and Aim: Arthropod ectoparasites (mites, lice, ticks, and fleas) on common house rats or brown rats (Rattus norvegicus) are known to transmit zoonotic pathogens and diminish rat health. To the best of our knowledge, there is no published information regarding the prevalence of ectoparasites on R. norvegicus in Grenada. This study aimed to determine the prevalence and types of ectoparasites present on brown rats from Grenada. Materials and Methods: One hundred sixty-eight rats were collected live from the parishes of St. George and St. David, Grenada, from May to July 2017. Following euthanasia, external parasites were collected using fine combs, thumb forceps, and paper tape. Tape samples and free specimens were placed in containers with 70% ethanol. External parasites were evaluated using dissection microscopy. Results: Over 2000 ectoparasites were collected from 149 of the 168 trapped rats (88.7%). Ectoparasites identified included mesostigmatid mites (found on 84.6% of infested rats), fur mites in the families Atopomelidae and Listrophoridae (67.1%), Polyplax spp. lice (6.7%), fleas (3.4%), an unidentified larval tick (0.7%), and a mite in the family Myobiidae (0.7%). Infestation rates were higher in St. David Parish (86/89; 96.6%) than in St. George Parish (63/79; 79.7%) (p=0.001). When comparing sex and age, males had a marginal increase in infestation rate (83/89; 93.3%) compared to females (66/79; 83.5%) (p=0.054), and adults had an infestation rate of 90.7% (97/107) compared to juvenile rats who had a 66.7% (14/21) infestation rate. Conclusion: Brown rats in Grenada are heavily infested with ectoparasites, including known vectors of pathogens. Future studies will examine the prevalence of zoonotic pathogens in these arthropods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".