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EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia
BACKGROUND: Electronic syndromic surveillance for early outbreak detection may be a simple, effective tool to rapidly bring reliable and actionable outbreak data to the attention of public health authorities in the developing world. METHODS: Twenty-nine signs and symptoms from patients with conditio...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2587689/ https://www.ncbi.nlm.nih.gov/pubmed/19025680 |
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author | Siswoyo, Hadi Permana, Meda Larasati, Ria P Farid, Jeffryman Suryadi, Asep Sedyaningsih, Endang R |
author_facet | Siswoyo, Hadi Permana, Meda Larasati, Ria P Farid, Jeffryman Suryadi, Asep Sedyaningsih, Endang R |
author_sort | Siswoyo, Hadi |
collection | PubMed |
description | BACKGROUND: Electronic syndromic surveillance for early outbreak detection may be a simple, effective tool to rapidly bring reliable and actionable outbreak data to the attention of public health authorities in the developing world. METHODS: Twenty-nine signs and symptoms from patients with conditions compatible with infectious diseases are collected from selected Provincial hospitals and analyzed daily. Data is e-mailed on a daily basis to a central data management and analysis center. Automated data analysis may be viewed at the hospital or the Early Warning Outbreak Response System (EWORS) hub at the central level (National Institute of Health Research and Development/NIHRD). CONCLUSION: The Indonesian Ministry of Health (MoH) has adopted EWORS since 2006 and will use it as a complementary surveillance tool in wider catchment areas throughout the country. Socialization to more users is still being conducted under collaboration of three Directorate Generals (DGs) of the MoH; DG of NIHRD, DG of Medical Services and DG of Communicable Disease Control and Prevention. Currently, EWORS is being adapted to facilitate detecting a potential outbreak of pandemic influenza in the region, and automated procedures for outbreak detection have been added. |
format | Text |
id | pubmed-2587689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-25876892008-11-26 EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia Siswoyo, Hadi Permana, Meda Larasati, Ria P Farid, Jeffryman Suryadi, Asep Sedyaningsih, Endang R BMC Proc Proceedings BACKGROUND: Electronic syndromic surveillance for early outbreak detection may be a simple, effective tool to rapidly bring reliable and actionable outbreak data to the attention of public health authorities in the developing world. METHODS: Twenty-nine signs and symptoms from patients with conditions compatible with infectious diseases are collected from selected Provincial hospitals and analyzed daily. Data is e-mailed on a daily basis to a central data management and analysis center. Automated data analysis may be viewed at the hospital or the Early Warning Outbreak Response System (EWORS) hub at the central level (National Institute of Health Research and Development/NIHRD). CONCLUSION: The Indonesian Ministry of Health (MoH) has adopted EWORS since 2006 and will use it as a complementary surveillance tool in wider catchment areas throughout the country. Socialization to more users is still being conducted under collaboration of three Directorate Generals (DGs) of the MoH; DG of NIHRD, DG of Medical Services and DG of Communicable Disease Control and Prevention. Currently, EWORS is being adapted to facilitate detecting a potential outbreak of pandemic influenza in the region, and automated procedures for outbreak detection have been added. BioMed Central 2008-11-14 /pmc/articles/PMC2587689/ /pubmed/19025680 Text en Copyright © 2008 Siswoyo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Siswoyo, Hadi Permana, Meda Larasati, Ria P Farid, Jeffryman Suryadi, Asep Sedyaningsih, Endang R EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title | EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title_full | EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title_fullStr | EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title_full_unstemmed | EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title_short | EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia |
title_sort | ewors: using a syndromic-based surveillance tool for disease outbreak detection in indonesia |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2587689/ https://www.ncbi.nlm.nih.gov/pubmed/19025680 |
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