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Probability of Disease Freedom Using Clustering Model

In development

The Probability of Disease Freedom Using Clustering Model is the third of three models used after sampling has occurred and no positive cases are found to estimate the latent prevalence of CWD.

Unlike the Simple Undetected Prevalence Estimator, which does not use any auxiliary information for prevalence estimation, or the Prevalence Estimator Data Export, which considers surveillance weights in prevalence estimation, the Probability Disease Freedom Using Clustering Model considers host clustering to estimate prevalence. Estimates hinge on the assumption that simple random sampling was used to select hosts from the landscape.

Geographical Scale

  • Administrative area, subdivided into a sub-administrative areas

Required Data

  • Population size or population density of hosts

User Inputs

  • Average cluster size of hosts
  • Correlation in disease status among hosts sharing a cluster
  • Sensitivity of the diagnostic test used to declare a CWD-positive case

Outputs

  • The probability that each sub-administrative area is disease-free

More Information

For more information, go to the CWD Data Warehouse User Manual: Probability of Disease Freedom Using Clustering Model.

Code

To view the code once deployed, go to the GitHub Repository: Probability of Disease Freedom Using Clustering Model.

Citations