SARS-CoV-2 in Namibian Dogs
Bibliographic record
Abstract
The pandemic of coronavirus disease 19 (COVID-19) has focused the attention of researchers, and especially public opinion, on the role of the human-animal-environment interface in disease emergence. At the beginning of the COVID-19 pandemic, media reports regarding the role of pets in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused significant concern and social anxiety. Although nowadays proven negligible in developed countries, essentially no studies have been performed in low-income African areas where companion animals are often raised differently from high income countries, and the contact patterns occurring in these scenarios could affect the epidemiological scenario. An extensive molecular biology survey was performed from March 2022 to September 2022 on Namibian dogs residing in urban and rural areas, showing a low but not negligible SARS-CoV-2 prevalence (1%; 95CI: 0.33-2.32%) of 5 out of 500. In only one instance (i.e., a 4-year-old female Labrador) was there a clear association that could be established between the infections of the owner and animal. In all other cases, no evidence of human infection could be obtained and no episodes of COVID-19 were reported by the owners. Although no consistent evidence of pet-to-pet transmission was proven in the present study, a cautionary principle suggests intensive and dedicated investigation into companion animal populations, especially when animal contact is frequent and a particularly susceptible population is present.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".