Evaluation of a Method for Detecting Aberrations in Public Health Surveillance Data
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...
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| Veröffentlicht in: | American journal of epidemiology 1993-02, Vol.137 (3), p.373-380 |
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| container_title | American journal of epidemiology |
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| creator | Stroup, Donna F. Wharton, Melinda Kafadar, Karen Dean, Andrew G. |
| description | 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. |
| doi_str_mv | 10.1093/oxfordjournals.aje.a116684 |
| format | Article |
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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.</description><subject>Bias</subject><subject>Biological and medical sciences</subject><subject>Data Interpretation, Statistical</subject><subject>Disease Outbreaks</subject><subject>epidemiologic methods</subject><subject>Epidemiology</subject><subject>General aspects</subject><subject>Humans</subject><subject>Medical sciences</subject><subject>Methodology</subject><subject>Models, Statistical</subject><subject>Morbidity</subject><subject>Organizational Objectives</subject><subject>Population Surveillance - methods</subject><subject>Public Health Administration - organization & administration</subject><subject>public health surveillance</subject><subject>Public health. Hygiene</subject><subject>Public health. 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Hygiene-occupational medicine</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stroup, Donna F.</creatorcontrib><creatorcontrib>Wharton, Melinda</creatorcontrib><creatorcontrib>Kafadar, Karen</creatorcontrib><creatorcontrib>Dean, Andrew G.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Periodicals Index Online Segment 24</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><collection>MEDLINE - Academic</collection><jtitle>American journal of epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stroup, Donna F.</au><au>Wharton, Melinda</au><au>Kafadar, Karen</au><au>Dean, Andrew G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of a Method for Detecting Aberrations in Public Health Surveillance Data</atitle><jtitle>American journal of epidemiology</jtitle><addtitle>Am J Epidemiol</addtitle><date>1993-02-01</date><risdate>1993</risdate><volume>137</volume><issue>3</issue><spage>373</spage><epage>380</epage><pages>373-380</pages><issn>0002-9262</issn><eissn>1476-6256</eissn><coden>AJEPAS</coden><abstract>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. 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| ispartof | American journal of epidemiology, 1993-02, Vol.137 (3), p.373-380 |
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| source | MEDLINE; Periodicals Index Online; Oxford Journals Archive |
| subjects | Bias Biological and medical sciences Data Interpretation, Statistical Disease Outbreaks epidemiologic methods Epidemiology General aspects Humans Medical sciences Methodology Models, Statistical Morbidity Organizational Objectives Population Surveillance - methods Public Health Administration - organization & administration public health surveillance Public health. Hygiene Public health. Hygiene-occupational medicine Sensitivity and Specificity |
| title | Evaluation of a Method for Detecting Aberrations in Public Health Surveillance Data |
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