Document Detail


Detection of aberrations in the occurrence of notifiable diseases surveillance data.
MedLine Citation:
PMID:  2540519     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
D F Stroup; G D Williamson; J L Herndon; J M Karon
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Statistics in medicine     Volume:  8     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  1989 Mar 
Date Detail:
Created Date:  1989-05-30     Completed Date:  1989-05-30     Revised Date:  2004-11-17    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  323-9; discussion 331-2     Citation Subset:  IM    
Affiliation:
Division of Surveillance and Epidemiologic Studies, Centers for Disease Control, Atlanta, Georgia 30333.
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MeSH Terms
Descriptor/Qualifier:
Centers for Disease Control and Prevention (U.S.)
Communicable Diseases / epidemiology*
Data Interpretation, Statistical*
Humans
Population Surveillance
Space-Time Clustering
United States

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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