Navigation and service

Use of cookies

Cookies help us to provide our services. By using our website you agree that we can use cookies. Read more about our Privacy Policy and visit the following link: Privacy Policy


Detection and Protection of epidemic situations (ESEG)

Syndromic Surveillance with Emergency Department Data


Within the scope of the ESEG project, near-real-time-data from emergency departments of selected hospitals throughout Germany shall be used for early identification of emerging outbreaks and other public health threats, to allow a timely introduction of infection protection or other necessary measures. It will be examined which added value is provided by a timely and hospital-overarching data collection, analysis and evaluation, compared to already existing surveillance systems.


The project is funded by the innovation fund of the Gemeinsamer Bundesausschuss (GBA) for 3 years (started in summer 2018). Lead by the local health authority of Frankfurt/Main, a network for syndromic surveillance based on emergency department data will be established. Joining different players from the public health sector, university research (Technische Universität Darmstadt, TU) and industry (software manufacturer epias GmbH), supported by about 30 partnering hospitals, the Robert Koch Institute (RKI) acts as the central partner for epidemiological evaluation.


Individual patient data from the routine documentation in emergency departments of selected hospitals will be transmitted anonymized in near-real-time to the study server (esegCU). The development of signal detection algorithms at the RKI will make use of available surveillance data on infectious diseases and methods of machine learning (at the TU Darmstadt).

Data flow in the ESEG project. Source: RKI Data flow in the ESEG project Source: RKI

Project partners and tasks

The ESEG project is led by the local health authority of Frankfurt/Main.

In the project, the RKI will be responsible for a number of different tasks, such as the programming of signal detection algorithms and the epidemiological evaluation of syndromic surveillance data for infectious diseases. Additionally, the newly introduced syndromic surveillance system will be adapted for high consequence infectious diseases (HCID), e.g. by defining specific symptoms and the evaluation of hygiene management processes within hospitals. Unit 31 "Infectious disease data science unit", unit 32 "Surveillance", unit 36 "Respiratory diseases" and ZBS 7 – Strategy and Incident Response are involved in the project at RKI.

For the initial development of this syndromic surveillance system, 30 hospitals with a central emergency department were selected throughout Germany. This cooperation is steered by the Sana Klinikum Offenbach GmbH.

The software manufacturer epias GmbH in Idstein is responsible for the programming of the interface, the browser-based environment for the primary data collection and the central study data base.

The Knowledge Engineering Group based in the Department for Information Technology at the TU Darmstadt will explore to what extent methods of machine learning can be used for signal detection.

With a focus to develop targeted and applicable output reports, the Hessisches Ministerium für Soziales und Integration and the Hessisches Landesprüfungs- und Untersuchungsamt im Gesundheitswesen support the project.

Further syndromic surveillcance systems and projects

Syndromic surveillance of acute respiratory diseases in Germany:

Syndromic surveillance in other European countries:

Date: 01.06.2021