PubMed · 9377216
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1997-03-15. CDC sets interim strategy for hepatitis A control.. https://doi.org/10.1093/ajhp%2F54.6.625
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Routine analysis of public health surveillance data to detect departures from historical patterns of disease frequency is required to enable timely public health responses to decrease unnecessary morbidity and mortality. We describe a monitoring system incorporating statistical 'flags' identifying unusually large increases (or decreases) in disease reports compared to the number of cases expected. The two-stage monitoring system consists of univariate Box-Jenkins models and subsequent tracking signals from several statistical process control charts. The analyses are illustrated on 1980-1995 national notifiable disease data reported weekly to the Centers for Disease Control and Prevention (CDC) by state health departments and published in CDC's Morbidity and Mortality Weekly Report. Published in 1999 by John Wiley & Sons, Ltd. This article is a U.S. Government work and is in the public domain in the United States.
This study examines the statistical properties (that is, false positive and negative signals) in detecting unusual patterns of reported cases of diseases from the Centers for Disease Control and Prevention's National Notifiable Diseases Surveillance System. Control charts are applied to the residuals of one-step ahead forecasts based on Box-Jenkins models of reported cases of disease. Simulation and analytical techniques are used to study the average run length characteristics of these control charts for various types of changes in the levels of the series, including spike, trend and step changes. The average run lengths for the highly correlated disease series are much longer than for the usual independent data case. This increase in the average run lengths is strongly influenced by the type of change in the level of the series and by the type of control chart. Understanding the average run length characteristics of the control charts can lead to timely detection of changes in the levels of disease series, and subsequent timely public health actions to decrease unnecessary morbidity and mortality.