title: ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands.
abstract: Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika virus outbreak.
  
  
  
  In the Netherlands, ICARES (Integrated Crisis Alert and Response System) has been developed and tested on three syndromes as an automated, real-time tool for early detection of clusters of infectious diseases. From local general practices, General Practice Out-of-Hours services and a hospital, the numbers of routinely used syndrome codes for three piloted tracts i.e., respiratory tract infection, hepatitis and encephalitis/meningitis, are sent on a daily basis to a central unit of infectious disease control. Historic data combined with information about patients' syndromes, age cohort, gender and postal code area have been used to detect clusters of cases.
  
  
  
  During the first 2 years, two out of eight alerts appeared to be a real cluster. The first was part of the seasonal increase in Enterovirus encephalitis and the second was a remarkably long lasting influenza season with high peak incidence.
  
  
  
  This tool is believed to be the first flexible automated, real-time cluster detection system for infectious diseases, based on physician information from both general practitioners and hospitals. ICARES is able to detect and follow small regional clusters in real time and can handle any diseases entity that is regularly registered by first line physicians. Its value will be improved when more health care institutions agree to link up with ICARES thus improving further the signal-to-noise ratio.
authors.affiliation: Department of Internal Medicine and Infectious Diseases, Leiden University Medical Center, P.O. box 9600, 2300 RC, Leiden, The Netherlands. g.h.groeneveld@lumc.nl.
authors.forename: Geert H
authors.initials: GH
authors.lastname: Groeneveld
authors.affiliation: Unit for Infectious Disease Control, Public Health Service Hollands Midden, Leiden, The Netherlands.
authors.forename: Anton
authors.initials: A
authors.lastname: Dalhuijsen
authors.affiliation: Faculty of Engineering and Informatics, University of Bradford, Bradford, UK.
authors.forename: Chakib
authors.initials: C
authors.lastname: Kara-Zaïtri
authors.affiliation: inFact, Shipley, UK.
authors.forename: Bob
authors.initials: B
authors.lastname: Hamilton
authors.affiliation: Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Margot W
authors.initials: MW
authors.lastname: de Waal
authors.affiliation: Centre for Infectious Disease Control, National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu, RIVM), Bilthoven, The Netherlands.|Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Jaap T
authors.initials: JT
authors.lastname: van Dissel
authors.affiliation: Centre for Infectious Disease Control, National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu, RIVM), Bilthoven, The Netherlands.|Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Jim E
authors.initials: JE
authors.lastname: van Steenbergen
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D003140:Communicable Disease Control / Q000379:methods*; D003141:Communicable Diseases / Q000453:epidemiology*; D000067498:Crew Resource Management, Healthcare / Q000379:methods*; D004196:Disease Outbreaks; D001330:Electronic Data Processing / Q000379:methods; D005260:Female; D006761:Hospitals; D006801:Humans; D015994:Incidence; D008297:Male; D009426:Netherlands / Q000453:epidemiology; D000071244:Zika Virus; D000071243:Zika Virus Infection / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control
keywords: Automated; Cluster detection; Hepatitis; Meningoencephalitis; Real-time; Respiratory tract infection