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ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands
BACKGROUND: 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 i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5345172/ https://www.ncbi.nlm.nih.gov/pubmed/28279150 http://dx.doi.org/10.1186/s12879-017-2300-5 |
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author | Groeneveld, Geert H. Dalhuijsen, Anton Kara-Zaïtri, Chakib Hamilton, Bob de Waal, Margot W. van Dissel, Jaap T. van Steenbergen, Jim E. |
author_facet | Groeneveld, Geert H. Dalhuijsen, Anton Kara-Zaïtri, Chakib Hamilton, Bob de Waal, Margot W. van Dissel, Jaap T. van Steenbergen, Jim E. |
author_sort | Groeneveld, Geert H. |
collection | PubMed |
description | BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. |
format | Online Article Text |
id | pubmed-5345172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53451722017-03-14 ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands Groeneveld, Geert H. Dalhuijsen, Anton Kara-Zaïtri, Chakib Hamilton, Bob de Waal, Margot W. van Dissel, Jaap T. van Steenbergen, Jim E. BMC Infect Dis Technical Advance BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2017-03-09 /pmc/articles/PMC5345172/ /pubmed/28279150 http://dx.doi.org/10.1186/s12879-017-2300-5 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Technical Advance Groeneveld, Geert H. Dalhuijsen, Anton Kara-Zaïtri, Chakib Hamilton, Bob de Waal, Margot W. van Dissel, Jaap T. van Steenbergen, Jim E. ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title | ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title_full | ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title_fullStr | ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title_full_unstemmed | ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title_short | ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands |
title_sort | icares: a real-time automated detection tool for clusters of infectious diseases in the netherlands |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5345172/ https://www.ncbi.nlm.nih.gov/pubmed/28279150 http://dx.doi.org/10.1186/s12879-017-2300-5 |
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