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Sample Allocation Model

The Sample Allocation Model (SAM) uses optimal control theory to identify an optimal surveillance strategy for areas with no cases of CWD, balancing surveillance costs and the probability of CWD introduction into each area. The SAM framework provides three model settings that allow users to flexibly integrate the probability of disease spread with any historical sampling data and/or expense data to understand (1) the probability that any given area is disease-free at present, and (2) how to best allocate a surveillance budget to be able to identify the introduction of CWD as early as possible.

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 or at a certain level of prevalence
  • A map containing the intensity of sampling needed in each sub-administrative area to achieve optimal control
  • A graph showing how different annual budgets affect the time to 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.