A Retrospective Analysis Reveals That the 2021 Outbreaks of African Swine Fever Virus in Ghana Were Caused by Two Distinct Genotypes
Bibliographic record
Abstract
African swine fever virus (ASFV) is the causative agent of African swine fever (ASF), a highly infectious and lethal disease of domesticated swine. Outbreaks of ASF have been mostly restricted to the continent of Africa. The outbreaks that have occurred outside of Africa were controlled by extensive depopulation of the domesticated pig population. However, in 2007, an outbreak occurred in the country of Georgia, where ASFV infected wild pigs and quickly spread across eastern Europe. Since the reintroduction of ASF into Europe, variants of the current pandemic strain, ASFV Georgia 2007/01 (ASFV-G), which is classified as Genotype 2 based on p72 sequencing, have been reported in countries within western Europe, Asia, and the island of Hispaniola. Additionally, isolates collected in 2020 confirmed the presence of variants of ASFV-G in Nigeria. Recently, we reported similar variants of ASFV-G collected from domestic pigs suspected of dying of ASF in Ghana in 2022. Here, we retroactively report, based on full-length sequencing, that similar variants were present in Ghana in 2021. The SNP analysis revealed derivatives of ASFV with distinct genetic markers. Furthermore, we identified three full-length ASFV genomes as Genotype 1, indicating that there were two genotypes circulating in proximity during the 2021 ASF outbreaks in Ghana.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".