Evidence map›Paper›PMID 41645798›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2026

Design and implementation of an evaluation framework for the Epidemic Intelligence from Open Sources (EIOS) system for international public health intelligence at the Robert Koch Institute, Germany, 2023.

Mario Martín-Sánchez, Sarah Esquevin, Andreas Jansen, Sofie Gillesberg Lassen

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Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mario Martín-SánchezECDC Fellowship Programme, Field Epidemiology path (EPIET), European Centre for Disease Prevention and Control (ECDC), Stockholm, Sweden.
Sarah EsquevinCentre for International Health Protection (ZIG), Robert Koch Institute (RKI), Berlin, Germany.
Andreas JansenCentre for International Health Protection (ZIG), Robert Koch Institute (RKI), Berlin, Germany.
Sofie Gillesberg LassenDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUNDPublic Health Intelligence (PHI) aims to detect health threats early for a timely and effective response. The PHI team at the Robert Koch Institute (RKI) uses the Epidemic Intelligence from Open Sources (EIOS) system in combination with other sources for detecting signals of international public health threats relevant to Germany. However, while EIOS is increasingly used for PHI worldwide, it is rarely evaluated.AIMWe designed and conducted an attribute-based evaluation to assess EIOS's performance for international PHI in 2023 and to identify areas for improvement.METHODSWe adapted surveillance system attributes and designed attribute-specific data collection methods. We conducted a mixed-method evaluation combining prospective and retrospective operational data collection with feedback from PHI officers.RESULTSDuring 2 weeks in July 2023, the PHI team reported 20 signals: 16 detected using EIOS and four from other sources. Increasing the number of EIOS sources increased timeliness and sensitivity slightly but caused a 35-fold increase in articles to screen (35,546 vs 1,138). The team found EIOS flexible and simple for signal detection but identified challenges in simplicity of signal documenting and reporting and in completeness of EIOS sources screened by the team.CONCLUSIONThe current use of EIOS proved sensitive and timely. However, PHI must balance sensitivity, timeliness and resource requirements. To maintain this balance, we strongly recommend regular evaluations of the use of EIOS for PHI. Our evaluation offers practical guidance for other PHI teams. We recommend integrating EIOS with an event management system to facilitate signal documentation and reporting.

Indexed as

Disease OutbreaksEpidemicsPopulation SurveillancePublic HealthPublic Health SurveillanceData CollectionGermanyHumansProspective StudiesPublic Health InfrastructureRetrospective StudiesEIOSEvaluationEvent-based surveillancePandemic PreparednessPublic Health Surveillance

Identifiers

PMID41645798
PMCPMC12881845

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.