Household transmission of SARS-CoV-2 from humans to pets in Washington and Idaho: burden and risk factors
Bibliographic record
Abstract
SARS-CoV-2 is believed to have emerged from an animal reservoir; however, the frequency of and risk factors for inter-species transmission remain unclear. We carried out a community-based study of pets in households with one or more confirmed SARS-CoV-2 infection in humans. Among 119 dogs and 57 cats with completed surveys, clinical signs consistent with SARS-CoV-2 were reported in 20 dogs (21%) and 19 cats (39%). Out of 81 dogs and 32 cats sampled for testing, 40% of dogs and 43% of cats were seropositive, and 5% of dogs and 8% of cats were PCR positive; this discordance may be due to delays in sampling. Respondents commonly reported close human-animal contact and willingness to take measures to prevent transmission to their pets. Reported preventative measures showed a slightly protective trend for both illness and seropositivity in pets, while sharing of beds and bowls had slight harmful effects.
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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 | 0.001 | 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".