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Assessing intrastate shipments from interstate data and expert opinion.

Peter Brommesson1, Stefan Sellman1, Lindsay Beck-Johnson2

  • 1Department of Physics, Chemistry and Biology, Division of Theoretical Biology, Linköping University, 58183 Linköping, Sweden.

Royal Society Open Science
|May 7, 2021
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Summary

Estimating animal disease spread requires complete contact networks, which are often unavailable. This study models intrastate animal shipments using veterinary inspection data and expert opinions, revealing preferred spatial kernel shapes for accurate predictions.

Keywords:
cattle shipmentexpert datalivestockmovement networkspread of disease

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Area of Science:

  • Veterinary epidemiology
  • Disease transmission modeling
  • Animal health surveillance

Background:

  • Live animal movements are critical for infectious disease spread between animal holdings.
  • Complete contact network data for animal shipments are lacking in many regions, including the USA.
  • Accurate modeling of disease spread necessitates understanding intrastate shipment patterns.

Purpose of the Study:

  • To estimate unobserved intrastate animal shipments in the USA.
  • To evaluate the impact of different spatial kernel functional forms on shipment predictions.
  • To assess the utility of expert elicitation data in improving disease spread models.

Main Methods:

  • Analysis of a 10% sample of Interstate Certificate of Veterinary Inspections from 2009.
  • Hierarchical Bayesian modeling to estimate spatial kernel parameters.
  • Comparison of six models incorporating different spatial kernel forms and expert data.

Main Results:

  • Predictions of intrastate shipments were moderately sensitive to the spatial kernel's functional form.
  • Spatial kernels with a 'fat tail' at long distances and a plateau at short distances were preferred.
  • Expert elicitation data did not consistently improve prediction accuracy when expert estimates were highly variable.

Conclusions:

  • The choice of spatial kernel functional form influences intrastate shipment predictions in disease modeling.
  • Understanding distance-dependent movement patterns is key for accurate animal disease spread assessments.
  • The value of expert data in epidemiological modeling depends on the consensus and quality of expert opinions.