Reporting incidence from a surveillance system with an operational case definition of unknown predictive value positive

Details

• Alternative Title:
  Epidemiol Perspect Innov
• Personal Author:
  Kegler, Scott R
• Description:
  When reporting incidence rate estimates for relatively rare health conditions, associated case counts are often assumed to follow a Poisson distribution. Case counts obtained from large-scale electronic surveillance systems are often inflated by the presence of false positives, however, and adjusted case counts based on the results of a validation sample will have variances which are hyper-Poisson. This paper presents a simple method for constructing interval estimates for incidence rates based on case counts that are adjusted downward using an estimate of the predictive value positive of the surveillance case definition.
• Subjects:
  Methodology
• Source:
  Epidemiol Perspect Innov. 2005; 2:7.
• Document Type:
  Journal Article
• Volume:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:6bfb668b21254c3aace90906ecef2759f5049e3a40cfd69ae804e25d40dad887b5986568a99e0b2628bb790e0448afd9383500c46b468cfd20fa29afdfdaaab9
• Download URL:
  https://stacks.cdc.gov/view/cdc/3610/cdc_3610_DS1.pdf
• File Type:
  [PDF - 217.44 KB ]