Emerging Infectious Disease ISSN: 1080-6059

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

L. C. Hutwagner, E. K. Maloney, N. H. Bean, L. Slutsker, and S. M. Martin

Author affiliations: Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Figure 1

Algorithm for outbreak detection for one serotype for 1 week.a aSince we are interested in detecting only increases in the number of isolates of Salmonella serotypes, we based our algorithm on a one-sided CUSUM. The numbers vary by serotype, and we assume the numbers of individual serotypes to be normally distributed for any given week in the past 5 years. A one-sided CUSUM determines a positive shift from the expected mean. The

Figure 1. ^{Algorithm for outbreak detection for one serotype for 1 week.a a}Since we are interested in detecting only increases in the number of isolates of Salmonella serotypes, we based our algorithm on a one-sided CUSUM. The numbers vary by serotype, and we assume the numbers of individual serotypes to be normally distributed for any given week in the past 5 years. A one-sided CUSUM determines a positive shift from the expected mean. The

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