Work

EWORS: using a syndromic-based surveillance tool for disease outbreak detection in Indonesia

Year: 2008

Type: article

Abstract: 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.

Source: BMC Proceedings

DOI: 10.1186/1753-6561-2-s3-s3

Authors: Hadi Siswoyo, Meda Permana, Ria P Larasati, Jeffryman Farid, Asep Suryadi, Endang R Sedyaningsih

Institution: Kementerian Kesehatan Republik Indonesia

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,290