Health and economic consequences: How COVID-19 affected households with pet and their pets. A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Households with pets had a unique experience with the COVID-19 since the lock-down protocols did not affect only the relationship they had with people but also with their pets. This paper analysed the evidence on the effect of COVID-19 on pets and pets owners. Employing the systematic review guidelines, the PubMed and the Google scholar database were utilised to select empirical studies published in English that focused on: (1) the COVID-19 effects on pets and (2) the COVID-19 effects on pet owners. We identified 24 articles conducted across 7 countries that met the eligibility criteria of the review. Few other studies used participants from multiple countries. Most of the studies utilised the cross-sectional survey and collected data from pet owners. Also, about 44.0% of the studies were published in only one journal (animal). COVID-19 affected the health status of both pets and pet owners. Despite the several negative health implications, there was some evidence of positive health implications. Surprisingly, several pet owners were not affected by the negative economic consequences of the pandemic. Recommendations for future studies were made in line with where attention is needed.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it