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A Retrospective Economic Analysis of the Ontario Red Fox Oral Rabies Vaccination Programme

2010· article· en· W2125266536 on OpenAlexafffundabout
Stephanie A. Shwiff, Christopher P. Nunan, Katy N. Kirkpatrick, Steven Shwiff

Bibliographic record

VenueZoonoses and Public Health · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsTrent UniversityMinistry of Natural Resources and Forestry
FundersMinistry of Natural ResourcesU.S. Department of Agriculture
KeywordsRabiesVulpesIndemnityVaccinationCost–benefit analysisEconomic analysisVeterinary medicineToxicologyMedicineEnvironmental healthBiologyVirologyBusinessAgricultural economicsEcologyEconomicsPredationActuarial science

Abstract

fetched live from OpenAlex

Ontario initiated a red fox (Vulpes vulpes) oral rabies vaccination (ORV) programme in 1989. This study utilized a benefit-cost analysis to determine if this ORV programme was economically worthwhile. Between 1979 and 1989, prior to ORV baiting, the average annual human post-exposure treatments, positive red fox rabies diagnostic tests and indemnity payments for livestock lost to rabies were 2248, 1861 and $246,809, respectively. After baiting, from 1990 to 2000, a 35%, 66% and 41% decrease in post-exposure treatments, animal rabies tests and indemnity payments was observed, respectively. These reductions were viewed as benefits of the ORV programme, whereas total costs were those associated with ORV baiting. Multiple techniques were used to estimate four different benefit streams and the total estimated benefits ranged from $35,486,316 to $98,413,217. The annual mean ORV programme cost was $6,447,720, with total programme costs of $77,372,637. The average benefit-cost ratios over the analysis period were .49, 1.06, 1.27 and 1.36, indicating overall programme efficiency in three of the four conservative scenarios.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.274
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2010
Admission routes3
Has abstractyes

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