title: An evaluation model for syndromic surveillance: assessing the performance of a temporal algorithm.
abstract: BACKGROUND
  Syndromic surveillance offers the potential to rapidly detect outbreaks resulting from terrorism. Despite considerable experience with implementing syndromic surveillance, limited evidence exists to describe the performance of syndromic surveillance systems in detecting outbreaks.
  
  
  OBJECTIVE
  To describe a model for simulating cases that might result from exposure to inhalational anthrax and then use the model to evaluate the ability of syndromic surveillance to detect an outbreak of inhalational anthrax after an aerosol release.
  
  
  METHODS
  Disease progression and health-care use were simulated for persons infected with anthrax. Simulated cases were then superimposed on authentic surveillance data to create test data sets. A temporal outbreak detection algorithm was applied to each test data set, and sensitivity and timeliness of outbreak detection were calculated by using syndromic surveillance.
  
  
  RESULTS
  The earliest detection using a temporal algorithm was 2 days after a release. Earlier detection tended to occur when more persons were infected, and performance worsened as the proportion of persons seeking care in the prodromal disease state declined. A shorter median incubation state led to earlier detection, as soon as 1 day after release when the incubation state was < or =5 days.
  
  
  CONCLUSIONS
  Syndromic surveillance of a respiratory syndrome using a temporal detection algorithm tended to detect an anthrax attack within 3-4 days after exposure if >10,000 persons were infected. The performance of surveillance (i.e., timeliness and sensitivity) worsened as the number of persons infected decreased.
authors.affiliation: Palo Alto Veterans Health Care, Palo Alto, California, USA. david.buckeridge@stanford.edu
authors.forename: David L
authors.initials: DL
authors.lastname: Buckeridge
authors.forename: P
authors.initials: P
authors.lastname: Switzer
authors.forename: D
authors.initials: D
authors.lastname: Owens
authors.forename: D
authors.initials: D
authors.lastname: Siegrist
authors.forename: J
authors.initials: J
authors.lastname: Pavlin
authors.forename: M
authors.initials: M
authors.lastname: Musen
mesh_terms: D000465:Algorithms; D000881:Anthrax / Q000453:epidemiology* / Q000517:prevention & control; D001408:Bacillus anthracis; D023482:Bioterrorism; D004196:Disease Outbreaks / Q000517:prevention & control*; D015991:Epidemiologic Measurements; D006801:Humans; D019570:Inhalation Exposure; D008962:Models, Theoretical; D011159:Population Surveillance / Q000379:methods*; D040442:Public Health Informatics; D013171:Spores, Bacterial