Seroprevalence of Dirofilaria immitis, feline leukemia virus, and feline immunodeficiency virus infection among dogs and cats exported from the 2005 Gulf Coast hurricane disaster area
Bibliographic record
Abstract
OBJECTIVE: To determine seroprevalence of dirofilariasis in dogs and seroprevalences of dirofilariasis, FeLV infection, and FIV infection in cats exported from the Gulf Coast region following the 2005 hurricanes. DESIGN: Seroprevalence survey. ANIMALS: 1,958 dogs and 1,289 cats exported from Louisiana, Mississippi, and Texas between August 20 and December 31, 2005. PROCEDURES: 141 animal welfare groups in 37 states and Alberta, Canada, reported results of serologic testing. Risk factors for infection, including age, sex, neuter status, breed, and state of rescue, were examined by means of univariate and multivariate logistic regression. RESULTS: Seroprevalence of dirofilariasis in dogs was 48.8%. Sexually intact dogs were 1.6 times as likely to have dirofilariasis as were neutered dogs, dogs in the ancient breed group were 2.2 times as likely and dogs in the guarding breed group were 1.7 times as likely to have dirofilariasis as were dogs in the herding breed group, and dogs from Mississippi were significantly less likely to have dirofilariasis than were dogs from Texas. Seroprevalences of dirofilariasis, FeLV infection, and FIV infection in cats were 4.0%, 2.6%, and 3.6%, respectively. Seroprevalence of FIV infection was significantly higher in adult cats than in juveniles and in males than in females. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that dogs and cats exported from the 2005 Gulf Coast hurricane disaster area had disease rates similar to those for animals in the region prior to the hurricanes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".