As we have demonstrated for SARS, GUARDIAN's infectiousdisease knowledge base uses robust models, which accurately discriminate among related diseases with a high level of accuracy, confidently place each diagnosis within its appropriate relative risk category and optimize its performance for a particular healthcare facility. These results illustrate the improvement that disease-specific expert systems, such as GUARDIAN, represent over traditional trend-based anomaly detection systems. The robust process presented here is currently being used to validate GUARDIAN's existing and ever-growing knowledge base containing a number of diseases of interest for public health surveillance. 