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    International One Health Symposium 2026

    Oct 5 – 7, 2026
    Hotel Berlin, Berlin
    Europe/Berlin timezone
    >> Safe the date for the next symposium: September 29 – October 1, 2027 <<

    Contact/Support: Orgalution GmbH

    GUARDIAN – One Health Surveillance for Predicting Antimicrobial Resistance: An AI-Based Pilot Project in Central Hesse

    Oct 6, 2026, 1:28 PM
    9m
    Hall "Berlin"

    Hall "Berlin"
    Oral presentation Research consortia on the topic of "Pandemic prevention and response within a One Health framework" (only for the Pandemic networks currently funded by the BMFTR) Session 7: Research consortia on the topic of “Pandemic prevention and response within a One Health framework”

    Speaker

    P. Fischer (Technische Hochschule Mittelhessen, University of Applied Sciences)

    Description

    Antimicrobial resistance (AMR) is a global health challenge that requires collaboration across human, animal, and environmental health. Yet surveillance data are often collected and analysed separately, limiting the early detection of emerging resistance patterns and transmission pathways.

    GUARDIAN is developing an AI-enabled One Health platform for the Central Hesse region. It integrates genomic, microbiological, clinical, epidemiological, environmental, and geospatial data to support predictive AMR surveillance.

    The project focuses on two contrasting scenarios: colistin resistance, closely associated with veterinary antimicrobial use, and carbapenem resistance, which is particularly relevant in human healthcare and hospital settings. Analysing both scenarios across sectors will help identify genetic links, transmission pathways, and regional patterns of spread. Data-driven models will be used to assess potential future developments.

    An interactive dashboard will visualise AMR trends and support public-health decision-making. By combining expertise from human and veterinary medicine, bioinformatics, public health, and environmental sciences, GUARDIAN aims to demonstrate how integrated One Health data and artificial intelligence can strengthen regional AMR surveillance.

    Registration ID OHS26
    Professional Status of the Speaker PhD Student
    Junior Scientist Status Yes, I am a Junior Scientist.

    Authors

    C. Ewers (Institut für Hygiene und Infektionskrankheiten der Tiere, Justus-Liebig-Universität Gießen, Deutschland.) T. Hain (Institut für Medizinische Mikrobiologie, Justus-Liebig-Universität Gießen, Deutschland.) C. Imirzalioglu (Institut für Medizinische Mikrobiologie, Justus-Liebig-Universität Gießen, Deutschland.) I. Bekerdjian-Ding (Institut für Medizinische Mikrobiologie und Krankenhaushygiene, Philipps-Universität Marburg, Deutschland.) T. Eisenberg (Landesbetrieb Hessisches Landeslabor, Gießen, Deutschland.) L. Falgenhauer (Hessisches Landesamt für Gesundheit und Pflege, Abteilung II, Gesundheits- und Infektionsschutz, Dillenburg, Deutschland.) J.-P. Mengel (Hessisches Landesamt für Gesundheit und Pflege, Abteilung II, Gesundheits- und Infektionsschutz, Dillenburg, Deutschland.) A. Goesmann (Bioinformatics and Systems Biology, Justus-Liebig-Universität Gießen, Deutschland.) N. van den Berg (Institut für Community Medicine, Versorgungsepidemiologie und Community Health, Universitätsmedizin Greifswald, Deutschland.) F. Eberhardt (Fachbereich Gesundheit, Technische Hochschule Mittelhessen, Gießen, Deutschland.) K. Sohrabi (Institut für Medizinische Informatik, Justus-Liebig-Universität Gießen, Deutschland.)

    Co-author

    P. Fischer (Technische Hochschule Mittelhessen, University of Applied Sciences)

    Presentation materials

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    External references

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