ASSESSING THE EFFICIENCY OF LOCAL RABIES VACCINATION STRATEGIES FOR RACCOONS (PROCYON LOTOR) IN AN URBAN SETTING
Bibliographic record
Abstract
Raccoon rabies virus (RRV) has been managed using multiple vaccination strategies, including oral rabies vaccination and trap-vaccinate-release (TVR). Identifying a rabies vaccination strategy for an area is a nontrivial task. Vaccination strategies differ in the amount of effort and monetary costs required to achieve a particular level of vaccine seroprevalence (efficiency). Simulating host movement relative to different vaccination strategies in silico can provide a useful tool for exploring the efficiency of different vaccination strategies. We refined a previously developed individual-based model of raccoon movement to evaluate vaccination strategies for urban Hamilton, Ontario, Canada. We combined different oral rabies vaccination baiting (hand baiting, helicopter, and bait stations) with TVR strategies and used GPS data to parameterize and simulate raccoon movement in Hamilton. We developed a total of 560 vaccination strategies, in consultation with the Ontario Ministry of Natural Resources and Forestry, for RRV control in Hamilton. We documented the monetary costs of each vaccination strategy and estimated the population seroprevalence. Intervention costs and seroprevalence estimates were used to calculate the efficiency of each strategy to meet targets set for the purpose of RRV control. Estimated seroprevalence across different strategies varied widely, ranging from less than 5% to more than 70%. Increasing bait densities (distributed using by hand or helicopter) led to negligible increase in seroprevalence. Helicopter baiting was the most efficient and TVR was the least efficient, but helicopter-based strategies led to lower levels of seroprevalence (6-12%) than did TVR-based strategies (17-70%). Our simulations indicated that a mixed strategy including at least some TVR may be the most efficient strategy for a local urban RRV control program when seroprevalence levels >30% may be required. Our simulations provide information regarding the efficiency of different vaccination strategies for raccoon populations, to guide local RRV control in urban settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".