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A study of the average run length characteristics of the National Notifiable Diseases Surveillance System

✍ Scribed by Lewis VanBrackle; G. David Williamson


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
106 KB
Volume
18
Category
Article
ISSN
0277-6715

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✦ Synopsis


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 Noti"able 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 in#uenced 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.