Continuous surveillance and viral discovery in animals and humans are a core component of a one-health approach to address recent viral reverse zoonoses
Bibliographic record
Abstract
Contemporary human and animal viruses have a broad or narrow host range-those with a broad host range are potentially transmitted from animals to humans (ie, zoonosis) or humans to animals (ie, reverse zoonosis). This Currents in One Health article reviews the recent reverse zoonoses involving Coronaviridae, Poxviridae, arboviruses, and, for nonhuman primate species, the human respiratory viruses. The prevention and control of reverse zoonoses are also reviewed. Coronaviruses continue to emerge as new zoonotic agents, including a canine coronavirus, CCoV-HuPn-2018, circulating in people at low levels, and a pangolin coronavirus, MjHKU4r-CoV-1, circulating in Malayan pangolins. Moreover, the risk for SARS-CoV-2 variants to mutate in animal reservoirs and reinfect humans is ongoing. In the case of mpox, the risk of reverse zoonosis is low and there are vaccines for use in humans at risk. The situation with arboviruses is as varied as the number of human arboviruses, and only yellow fever virus and dengue virus have licensed vaccines in the Americas. As for reverse zoonoses in endangered species, solutions require changing human behavior and policies at all levels impacting wildlife. Overall, continuous surveillance and viral discovery in humans and animals remain core components of a one-health approach to reduce and, where possible, eliminate zoonotic and reverse zoonotic diseases. Viral zoonosis and viral reverse zoonosis focusing on recent influenza A virus disease events in humans and other species are the subjects of the companion Currents in One Health by Kibenge, AJVR, June 2023.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".