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Sample Allocation Model

In development

The Sample Allocation Model (SAM) uses pioneering methods in optimal control theory to balance surveillance cost with introduction probability in each sub-administrative area to pinpoint the best possible surveillance strategy across the entire administrative area. SAM is also useful in determining the probability that a sub-administrative area is disease-free given up to three years of historical sampling intensity without finding a positive case.

Geographical Scale

  • Administrative area, subdivided into a sub-administrative areas

Required Data

  • Average surveillance cost-per-sample in each sub-administrative area
  • The ability to run the Risk-Weighted Surveillance Quotas Model to obtain introduction probabilities

User Inputs

  • Annual budget of the surveillance program across the entire administrative area

Outputs

  • A map containing the probability that each sub-administrative area is disease-free
  • A map containing the intensity of sampling needed in each sub-administrative area to achieve optimal control
  • A graph showing the annual budget necessary to shorten the time till first detection

More Information

For more information, go to the CWD Data Warehouse User Manual: Sample Allocation Model.

Code

To view the code once deployed, go to the GitHub Repository: Sample Allocation Model.

Citation

  • Wang J, Hanley B, Thompson N, Gong Y, Walsh D, Huang Y, Gonzalez-Crespo C, Booth J, Caudell J, Miller L, Schuler K. Strategic allocation of surveillance and prevention resources for emerging wildlife disease. In peer review.