Molecular epidemiology, evolution, and transmission dynamics of raccoon rabies virus in Connecticut
Bibliographic record
Abstract
In North America, raccoon rabies virus (RRV) is a public health concern due to its potential for rapid spread, maintenance in wildlife, and impact on human and domesticated animal health. RRV is an endemic zoonotic pathogen throughout the eastern USA. In 1991, an outbreak of RRV in Fairfield County, Connecticut, spread through the state and eventually throughout the Northeast and into Canada. Factors that contribute to, or curb, RRV transmission should be explored and quantified to guide targeted rabies control efforts, including the size and location of buffer zones of vaccinated animals. However, population dynamics and potential underlying determinants of rabies virus diversity and circulation in Connecticut have not been fully studied. In this study, we aim to (i) investigate RRV source-sink dynamics between Connecticut and surrounding states and provinces, (ii) explore the impact of the Connecticut River as a natural barrier to transmission, and (iii) characterize the genomic diversity and transmission dynamics in Connecticut. Using RRV whole-genome sequences collected from various host species between 1990 and 2020, we performed comparative genetic and Bayesian phylodynamic analyses at multiple spatial scales. We analyzed 71 whole-genome sequences from Connecticut, including 21 recent RRV specimens collected at the Connecticut Veterinary Medical Diagnostic Laboratory that we sequenced for this study. Our analyses revealed evidence of RRV incursions over the US-Canada border, including bidirectional spread between Quebec and Vermont. Additionally, we highlighted the importance of Connecticut and New York in seeding RRV transmission in eastern North America, including two introduction events from New York to Connecticut that resulted in sustained local transmission. While RRV transmission does occur across the Housatonic and Connecticut Rivers, we demonstrated the distinct presence of spatial structuring in the phylogenetic trees and characterized the directionality of RRV migration. The significantly higher mean transition rates from locations east to west of the Connecticut River, compared to west to east, may be leveraged in directing interventions to fortify these natural barriers. Ultimately, the findings of these international, regional, and state analyses can inform targeted control programs, vaccination efforts, and enhanced surveillance at borders of key viral sources and sinks.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".