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A monitoring system for detecting aberrations in public health surveillance reports

✍ Scribed by G. David Williamson; Ginner Weatherby Hudson

Publisher: John Wiley and Sons
Year: 1999
Tongue: English
Weight: 164 KB
Volume: 18
Category: Article
ISSN: 0277-6715
DOI: 10.1002/(sici)1097-0258(19991215)18:23<3283::aid-sim316>3.0.co;2-z

No coin nor oath required. For personal study only.

✦ Synopsis

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 &#ags' 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 noti"able 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 =eekly Report.

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