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Estimating the potential for disease spread in horses associated with an equestrian show in Ontario, Canada using an agent-based model

2017· article· en· W2780181421 on OpenAlexaffabout
Kelsey L. Spence, Terri L. O’Sullivan, Zvonimir Poljak, Amy L. Greer

Bibliographic record

VenuePreventive Veterinary Medicine · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOutbreakDemographyPsychological interventionAttendanceEquine influenzaMedicinePopulationDisease controlQuarantineAttack rateVeterinary medicineGeographyEnvironmental healthVirology

Abstract

fetched live from OpenAlex

Participation in equestrian shows provides opportunities for contact between horses, increasing the risk of disease introduction and spread within the population. The magnitude of a potential outbreak, and the impact of disease prevention and control strategies, can be estimated using simulation modeling. The objectives of this study were to (1) examine the potential spread of equine influenza in a network of horses associated with a 2-day equestrian show in Ontario, Canada; and (2) determine the effectiveness of several interventions during a simulated outbreak. A discrete-event, continuous-time, stochastic agent-based simulation model was constructed to represent horses associated with the show, including those in attendance at the show, and those that were not in attendance but co-boarded with attending horses at their home facilities. At the beginning of each simulation run, one random horse in attendance at the show was infected with equine influenza. In the absence of interventions, the median attack rate was 0.029 (IQR: 0.016-0.056; mean: 0.043; 95% CI: 0.040-0.044) and the average outbreak duration was 19.58 days (95% CI: 19.31-19.85). The most effective intervention was the implementation of either a 5-day or 14-day quarantine period, which both resulted in the same median attack rate of 0.0026 (IQR: 0.0013-0.0039), although the mean attack rates differed (mean: 0.0043, 95% CI: 0.0039-0.0046; and mean: 0.0029, 95% CI: 0.0028-0.0029; respectively). In instances where implementing either a 5-day or 14-day quarantine period would not be feasible, quarantine for shorter time periods was effective when combined with targeted increases in initial facility-level vaccine coverage. The combined implementation of a 2-day quarantine period and an increased vaccine coverage of 75% in facilities with four or more owners resulted in a median attack rate of 0.013 (IQR: 0.0052-0.026; mean: 0.022; 95% CI: 0.020-0.024). This study demonstrates a relative comparison of intervention effectiveness during a simulated outbreak of equine influenza in a population of horses associated with an equestrian show. The results have the potential to inform and improve the current strategies used to prevent the introduction and spread of disease within the equine population.

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 score0.310
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.136
GPT teacher head0.322
Teacher spread0.186 · 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

Citations9
Published2017
Admission routes2
Has abstractyes

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