Molecular epidemiology of lumpy skin disease virus in bovines: A one-year surveillance research
Bibliographic record
Abstract
Lumpy Skin Disease (LSD) has historically been confined to Africa and parts of the Middle East, but its geographic expansion over the past decade into Europe, Asia, and more recently into temperate zones of North America has prompted urgent surveillance efforts. This research describes the molecular epidemiology of Lumpy Skin Disease Virus (LSDV) across 38 cattle herds in three regions of Ontario, Canada, during a 12-month active surveillance programme conducted from March 2023 to February 2024. A total of 283 skin nodule biopsies and blood samples from clinically suspect animals were tested by real-time PCR targeting the P32 and RPO30 genes, yielding 38 confirmed positive herds and 146 individual animal-level positives. Monthly prevalence peaked at 21.2% during July, coinciding with maximum vector activity, and declined to below 2% by December. Phylogenetic analysis of 42 complete GPCR gene sequences placed all Ontario isolates within a single genetic cluster most closely related to the Neethling-like lineage previously reported in southeastern Europe, separated by 12 to 18 SNPs from the vaccine strain. Sequence data from three geographic sub-clusters suggested at least two independent introduction events into the province. Molecular clock estimates dated the most recent common ancestor of the Ontario clade to approximately mid-2022. These findings confirm the establishment of LSDV in temperate North American cattle populations, demonstrate a strong seasonal pattern linked to arthropod vector abundance, and underline the need for sustained genomic surveillance to track viral evolution and inform vaccination strategy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".