Unifying the spatial population dynamics and molecular evolution of epidemic rabies virus
Bibliographic record
Abstract
Infectious disease emergence is under the simultaneous influence of both genetic and ecological factors. Yet, we lack a general framework for linking ecological dynamics of infectious disease with underlying molecular and evolutionary change. As a model, we illustrate the linkage between ecological and evolutionary dynamics in rabies virus during its epidemic expansion into eastern and southern Ontario. We characterized the phylogeographic relationships among 83 isolates of fox rabies virus variant using nucleotide sequences from the glycoprotein-encoding glycoprotein gene. The fox rabies virus variant descended as an irregular wave with two arms invading from northern Ontario into southern Ontario over the 1980s and 1990s. Correlations between genetic and geographic distance suggest an isolation by distance population structure for the virus. The divergence among viral lineages since the most recent common ancestor correlates with position along the advancing wave front with more divergent lineages near the origin of the epidemic. Based on divergence from the most recent common ancestor, the regional population can be partitioned into two subpopulations, each corresponding to an arm of the advancing wave. Subpopulation A (southern Ontario) showed reduced isolation by distance relative to subpopulation B (eastern Ontario). The temporal dynamics of subpopulation A suggests that the subregional viral population may have undergone several smaller waves that reduced isolation by distance. The use of integrated approaches, such as the geographical analysis of sequence variants, coupled with information on spatial dynamics will become indispensable aids in understanding patterns of disease emergence.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".