Safety and Immunogenicity of Morbillivirus canis Vaccines for Domestic and Wild Animals: A Scoping Review
Bibliographic record
Abstract
Morbillivirus canis (canine distemper virus (CDV)) is recognized as a multihost pathogen responsible for a transmissible disease affecting both domestic and wild animals. A considerable portion of wildlife populations remain unvaccinated due to a lack of safety and immunogenicity data on existing vaccines for the prevention of CDV infection in these species. This review aimed to assess the current state of CDV vaccination research for both domestic and wild animals and to explore novel vaccine candidates through in vivo studies. It also sought to synthesize the scattered information from the extensive scientific literature on CDV vaccine research, identify key researchers in the field, and highlight areas where research on CDV vaccination is lacking. A scoping review was conducted across four databases following the PRISMA-ScR protocol, with information analyzed using absolute and relative frequencies and 95% confidence intervals (CIs) for study number proportions. Among the 2321 articles retrieved, 68 met the inclusion criteria and focused on CDV vaccines in various animal species, such as dogs, ferrets, minks, and mice. Most of the scientific community involved in this research was in the USA, Canada, France, and Denmark. Various vaccine types, including MLV CDV, recombinant virus, DNA plasmids, inactivated CDV, and MLV measles virus (MeV), were identified, along with diverse immunization routes and schedules employed in experimental and commercial vaccines. Safety and efficacy data were summarized. Notably, 37 studies reported postimmunization CDV challenge, primarily in dogs, revealing the survival rates of vaccinated animals. In summary, CDV vaccines generally demonstrate an acceptable safety profile in dogs and show promise as a means of controlling CDV. However, significant gaps in vaccine research persist, particularly concerning wildlife reservoirs, indicating the need for further investigation.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".