Detection of aberrations in the occurrence of notifiable diseases surveillance data.
The detection of unusual patterns in the occurrence of diseases and other health events presents an important challenge to public health surveillance. This paper discusses three analytic methods for identifying aberrations in underlying distributions. The methods are illustrated on selected infectious diseases included in the National Notifiable Diseases Surveillance System of the Centers for Disease Control. Results suggest the utility of such an analytic approach. Further work will determine the sensitivity of such methods to variations in the occurrence of disease. These methods are useful for evaluating and monitoring public health surveillance data.
Stroup
D F
DF
Division of Surveillance and Epidemiologic Studies, Centers for Disease Control, Atlanta, Georgia 30333.
Williamson
G D
GD
Herndon
J L
JL
Karon
J M
JM
D002487:Centers for Disease Control and Prevention, U.S.; D003141:Communicable Diseases / Q000453:epidemiology*; D003627:Data Interpretation, Statistical; D006801:Humans; D011159:Population Surveillance; D013029:Space-Time Clustering; D014481:United States