Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, USA, 2014–2015

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  Greene, Sharon K. ; Peterson, Eric R. ; Kapell, Deborah ; Fine, Annie D. ; Kulldorff, Martin
• Description:
  Each day, the New York City Department of Health and Mental Hygiene uses the free SaTScan software to apply prospective space-time permutation scan statistics to strengthen early outbreak detection for 35 reportable diseases. This method prompted early detection of outbreaks of community-acquired legionellosis and shigellosis.
• Subjects:
  Adolescent Adult Aged Aged, 80 And Over Child Child, Preschool Communicable Disease Control/methods Disease Notification Disease Outbreaks/prevention & Control Dispatch Dysentery, Bacillary/epidemiology Female Humans Infant Infant, Newborn Legionellosis/epidemiology Male Middle Aged Population Surveillance Space-Time Clustering Statistics As Topic Young Adult

  More +
• Source:
  Emerg Infect Dis. 22(10):1808-1812.
• Pubmed ID:
  27648777
• Pubmed Central ID:
  PMC5038417
• Document Type:
  Journal Article
• Place as Subject:
  New York City, NY
• Location:
  North America
• Volume:
  22
• Issue:
  10
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:bcaf620146384a6fea06c80dd68dc92a205ab09da391a839b46fe18938edeca6
• Download URL:
  https://stacks.cdc.gov/view/cdc/42750/cdc_42750_DS1.pdf
• File Type:
  [PDF - 936.72 KB ]