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 conditions...

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Bibliographic Details
Published in:BMC proceedings Vol. 2; no. Suppl 3; p. S3
Main Authors: Siswoyo, Hadi, Permana, Meda, Larasati, Ria P, Farid, Jeffryman, Suryadi, Asep, Sedyaningsih, Endang R
Format: Journal Article
Language:English
Published: London BioMed Central 14.11.2008
Subjects:
Biomedicine
Medicine
Medicine & Public Health
Proceedings
Leptospirosis
Syndromic Surveillance
District Health Office
Dengue Hemorrhagic Fever
Pandemic Influenza
ISSN:1753-6561, 1753-6561
Online Access:Get full text
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Summary: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.
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ISSN:1753-6561
1753-6561
DOI:10.1186/1753-6561-2-s3-s3