Using Laboratory-Based Surveillance Data for Prevention: An Algorithm for Detecting Salmonella Outbreaks

摘要: By applying cumulative sums (CUSUM), a quality control method commonly used in manufacturing, we constructed process for detecting unusual clusters among reported laboratory isolates of disease-causing organisms. We developed computer algorithm based on minimal adjustments to the CUSUM method, which cumulates differences between frequencies and their expected means; identify outbreaks Salmonella Enteritidis 1993. comparing these detected with known outbreaks, estimated sensitivity, specificity, false-positive rate method. Sensitivity by state outbreak was 0%(0/1) 100%. Specificity 64% 100%, 0 1.