Coronaviruses in wild rodent and eulipotyphlan small mammals: a review of diversity, ecological implications and surveillance considerations
Bibliographic record
Abstract
Coronaviruses are abundant and diverse RNA viruses with broad vertebrate host ranges. These viruses include agents of human seasonal respiratory illness, such as human coronaviruses OC43 and HKU1; important pathogens of livestock and domestic animals such as swine acute diarrhoea syndrome coronavirus and feline coronavirus; and human pathogens of epidemic potential such as SARS-CoV, MERS-CoV and SARS-CoV-2. Most coronavirus surveillance has been conducted in bat species. However, small terrestrial mammals such as rodents and eulipotyphlans are important hosts of coronaviruses as well. Although fewer studies of rodent and eulipotyphlan coronaviruses exist compared to those of bats, notable diversity of coronaviruses has been reported in the former. No literature synthesis for this area of research has been completed despite (a) growing evidence for a small mammal origin of certain human coronaviruses and (b) global abundance of small mammal species. In this review, we present an overview of the current state of coronavirus research in wild terrestrial small mammals. We conducted a literature search for studies that investigated coronaviruses infecting rodent and eulipotyphlan hosts, which returned 63 studies published up to and including 2024. We describe trends in coronavirus diversity and surveillance for these studies. To further the examination of the interrelatedness of these viruses, we conducted a phylogenetic analysis of coronavirus whole genomes recovered from rodent and eulipotyphlan hosts. We discuss important facets of terrestrial small mammal coronaviruses, including evolutionary aspects and zoonotic spillover risk. Lastly, we present important recommendations and considerations for further surveillance and viral characterization efforts in this field.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".