Positive Predictor Model (in development)

The Positive Predictor uses machine learning in conjunction with regional surveillance data to predict which sub-aministrative areas may turn CWD-positive in upcoming years.

Geographical Scale

• Sub-administrative areas

Required Data

• Sample data

Suggested Data

• Demography data
• Cervid facility data
• Taxidermist data
• Meat processor data

User Inputs

• Season-year

Outputs

• A map containing the predictions of CWD emergence for each county in the study area.

For more details, go to the CWD Data Warehouse User Manual: Positive Predictor Model.