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American Journal of Epidemiology Vol. 137, No. 3: 373-380
Copyright © 1993 by The Johns Hopkins University School of Hygiene and Public Health

research-article

Evaluation of a Method for Detecting Aberrations in Public Health Surveillance Data

Donna F. Stroup1,, Melinda Wharton2, Karen Kafadar3 and Andrew G. Dean1

1Division of Surveillance and Epidemiology, Epdemiology Program Office, Centers for Disease Control and Prevention Atlanta, GA
2National Center for Prevention Services, Centers for Disease Control and Prevention Atlanta, GA
3Division of Cancer Prevention and Control, National Cancer Institute Bethesda, MD

Reprint requests to Dr. Donna F Stroup, Division of Surveillance and Epidemiology, Epidemiology Program Office, Mail Stop C08, Centers for Disease Control and Prevention, 1600 Clifton Road NE, Atlanta. GA 30333

The detection of unusual patterns in routine public health surveillance data on diseases and injuries presents an important challenge to health workers interested in early identification of epidemics or clues to important risk factors. Each week, state health departments report the numbers of cases of about 50 notifiable diseases to the Centers for Disease Control and Prevention, and these reports are published weekly in the Morbidity and Mortality Weekly Report. A new analytic method and a horizontal bar graph were introduced in July 1989 to facilitate easy identification of unusual numbers of reported cases. Evaluation of the statistical properties of this method indicates that the results are fairly robust to nonnormality and serial correlation of the data. An epidemiologic evaluation of the method after the first 6 months showed that it is useful for detection of specific types of aberrations in public health surveillance.

epidemiologic methods; public health surveillance


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