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Project Groups

In line with the 1997 recommendations of the German Science Council a flexible Project Group structure was established within RKI. Its goal is a targeted focusing of research on selected areas, regardless of other acute research requirements. The topics covered include interdisciplinary issues which have a medium and long-term impact on the health protection of the population. The activities of the Project Groups are linked to the research in the different departments.

P 1: Risk Communication

Logo Risk Communication Unit, Source: RKIThe coronavirus pandemic has shown how difficult it is to communi­cate the facts, risks and un­cer­tain­ties around health topics effec­tively and with trans­parence. In the Risk Communication project group we work with research results and information out of the Robert Koch Institute in order to present them in an appropriate manner to various target groups. To this end, we use methods from empirical cognitive and be­havioural sciences, such as the develop­ment and testing of various communi­cation formats and media.


P 2: Acinetobacter baumannii – Biology of a Nosocomial Pathogen

Eine Kolonie von Acinetobacter baumannii, die sich über die Oberfläche eines Nährbodens ausbreitet. Quelle: © RKIAcinetobacter baumannii and related species such as A. pittii and A. nosocomialis are Gram-negative bacteria that appear as opportunistic pathogens in hospitals where they constitute a serious threat especially to immuno-compromised patients. They can cause ventilator-associated pneumonia, infections of wounds, soft-tissue and the urinary tract as well as sepsis and meningitis. In many countries they increasingly appear as multidrug resistant pathogens, restricting therapeutic options more and more.


P 4: Computational Epidemiology

Screen of the interactive tool to model the relative import risk of ebola virus disease. © Prof. Brockmann / Robert Koch Institute; Humboldt University BerlinUsing computational, theoretical and data-driven techniques from physics, computer science, dynamical systems theory, complex networks theory and complexity science we develop computational and theoretical models to improve our understanding of the dynamics, proliferation and evolution of infectious diseases. These models are designed to advance our understanding of basic mechanism and observed phenomena on a fundamental level. Based on mechanistic, data-driven models we design and build large scale computational models and forecast infrastructures that serve as predictive tools in the context of emergent outbreak scenarios.


P 5: Systems medicine of infectious diseases

artistic depiction of the evolutionary space of HIV-1 subtype B (nodes = variants; edges = edit distance. Source: © Max von Kleist/RKI"Systems medicine of infectious diseases" aims to better understand infection and transmission mechanisms, as well as evolutionary dynamics, and to describe them using methods from the field of data science and mathematical modeling. This serves both to create basic knowledge and to better evaluate prevention-, treatment- and surveillance strategies. Our work ranges from the mathematical formulation of the problem, the development or adaptation of algorithms, the evaluation on biomedical data to the implementation and publication of open source software.


P 6: Metabolism of microbial pathogens

Toxoplasma gondii tachyzoites. Source: © RKIPersistence of pathogens is a hallmark of many zoonotic infections with bacterial, fungal and parasitic pathogens. These infections remain difficult to treat medically. To study persistence and facilitate the development of new chemotherapies, we established a human skeletal muscle-based system allowing us to study the persisting bradyzoite stage of Toxoplasma gondii in vitro.