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

Siswoyo H, Permana M, Larasati RP, Farid J, Suryadi A, Sedyaningsih ER - BMC Proc (2008)

Bottom Line: 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).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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Biomedic and Pharmacy Research Center, National Institute of Health Research and Development, Indonesian Ministry of Health, Jakarta, Indonesia. hadisis@litbang.depkes.go.id

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.

No MeSH data available.


Related in: MedlinePlus

Number of cases with the symptom: fever, cutaneous bleeding, rash cough, sore throat, conjunctivitis in RSPI Sulianti Saroso Hospital, Jakarta, 01 January 2003 – 31 December 2006.
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Figure 2: Number of cases with the symptom: fever, cutaneous bleeding, rash cough, sore throat, conjunctivitis in RSPI Sulianti Saroso Hospital, Jakarta, 01 January 2003 – 31 December 2006.

Mentions: Two examples of how the system worked are described here. In the first example, EWORS detected a large DHF outbreak in 2003 that showed a moving trend across Indonesia from west to east. It started in Medan (Sumatera Island) in the west, spread to Jakarta (Java Island) and then to Bali Island. It also spread to Makassar, Sulawesi Province, in the north. What we observed was an excess of fever hemorrhagic cases starting in Medan in November 2003 (Figure 2), followed a month later by excess of similar cases in Jakarta in December 2003. A month later, an excess of fever hemorrhagic cases were noted in Bali, and in February 2004, excess cases were detected in Makassar. In the second example, EWORS was also able to detect a Leptospirosis outbreak (a combination of fever and jaundice) in Jakarta in 2006.


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

Siswoyo H, Permana M, Larasati RP, Farid J, Suryadi A, Sedyaningsih ER - BMC Proc (2008)

Number of cases with the symptom: fever, cutaneous bleeding, rash cough, sore throat, conjunctivitis in RSPI Sulianti Saroso Hospital, Jakarta, 01 January 2003 – 31 December 2006.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2587689&req=5

Figure 2: Number of cases with the symptom: fever, cutaneous bleeding, rash cough, sore throat, conjunctivitis in RSPI Sulianti Saroso Hospital, Jakarta, 01 January 2003 – 31 December 2006.
Mentions: Two examples of how the system worked are described here. In the first example, EWORS detected a large DHF outbreak in 2003 that showed a moving trend across Indonesia from west to east. It started in Medan (Sumatera Island) in the west, spread to Jakarta (Java Island) and then to Bali Island. It also spread to Makassar, Sulawesi Province, in the north. What we observed was an excess of fever hemorrhagic cases starting in Medan in November 2003 (Figure 2), followed a month later by excess of similar cases in Jakarta in December 2003. A month later, an excess of fever hemorrhagic cases were noted in Bali, and in February 2004, excess cases were detected in Makassar. In the second example, EWORS was also able to detect a Leptospirosis outbreak (a combination of fever and jaundice) in Jakarta in 2006.

Bottom Line: 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).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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Biomedic and Pharmacy Research Center, National Institute of Health Research and Development, Indonesian Ministry of Health, Jakarta, Indonesia. hadisis@litbang.depkes.go.id

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.

No MeSH data available.


Related in: MedlinePlus