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ASSOCIATED PROJECTS 

>     MEDIcow – Individualisierte Mastitis-Risikoeinschätzung in der Milchviehhaltung durch Sensoren, Digitalisierung und künstliche Intelligenz <     MEDIcow – Individualisierte Mastitis-Risikoeinschätzung in der Milchviehhaltung durch Sensoren, Digitalisierung und künstliche Intelligenz

MEDIcow – Individualisierte Mastitis-Risikoeinschätzung in der Milchviehhaltung durch Sensoren, Digitalisierung und künstliche Intelligenz

The aim of the German-Irish cooperation project MEDICow is to develop a tool for early, individualised mastitis detection for dairy cows based on a multisensory approach. With the help of various methods from the field of artificial intelligence (AI), a highly sensitive mastitis risk assessment is to be made possible, thus significantly shortening the time between infection and treatment. As part of the project, the newly developed molecular mastitis detection methods are also to be tested and included in the project if they are suitable as a rapid test. A real-time decision support model is then to be developed based on the linking of sensor and analysis data. By linking historical data with current data in the form of neural networks and other AI methods, it should also be possible to issue warnings about animals at particular risk of disease. The inclusion of Irish udder health data should provide information on the influence of various husbandry conditions and weather influences on udder health. The MEDICow model should also be applicable to dairy farms with conventional milking technology.

Start: 01.11.2021
End: 31.10.2024

Coordinating Institute

  • Leibniz Institute for Agriculture Engineering and Bioeconomy (ATB)

Coordination

Partners

  • Teagasc
  • Freie Universität Berlin
  • German Collection of Microorganisms and Cell Cultures GmbH (Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH)

Projectteam ATB

Further information can be found here.

 

 

>     ENVIRE - Interventions to control the dynamics of antimicrobial resistance from chickens through the environment <     ENVIRE - Interventions to control the dynamics of antimicrobial resistance from chickens through the environment

ENVIRE - Interventions to control the dynamics of antimicrobial resistance from chickens through the environment

We will carry out intervention studies, either as an experiment or in chicken farms. We will test, which interventions are most effective and feasible: i) Antibiotic-free raising of chickens, ii) Treatment with medicinal plants as alternative for antibiotics, iii) vaccination against the bacterium Escherichia coli, iv) Application of bacteriophages that infiltrate and destroy bacteria, v) Treatment or long storage of manure, vi) Treatment of farm effluents to remove antibiotics and their residues.

Focus will be laid on certain bacteria that are widely distributed, and on certain resistances that can harm human health (e.g. so-called ESBL). A mathematical risk assessment model will be developed and used to assess the effectiveness as well as potential synergistic effects of the interventions, to reduce human exposure via the foodborne, occupational and environmental pathways. Data already available for the participating countries will be included in the model, and new, essential data will be generated within the studies. As a result, specific as well as general interventions will be identified that have the potential to reduce AMR in chicken and in the environment of chicken farms for Europe and Tunisia. To achieve this, six working groups from Germany, France, Lithuania, Poland, and Tunisia, bundle their leading expertise for the respective issue. 

 

Project partners

  • Roswitha Merle, Freie Universität Berlin, Germany (Coordinator)
  • Lucie Collineau, French Agency for Food, Environmental and Occupational Health & Safety, France
  • Mindaugas Malakauskas, Veterinary Academy of Lithuanian University of Health Sciences, Lithuania
  • Marta Kuzminska-Bajor, Wroclaw University of Environmental and Life Sciences, Poland
  • Wejdene Mansour, University of Sousse, Tunisia
  • Tina Kabelitz, Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany

Further information can be found  here.

 

 

 

SEED MONEY PROJECTS (SMP)

>     SMP1: Characterization of antimicrobial resistance-carrying genomes from waterbodies and sediments using PacBio long-read sequencing technology <     SMP1: Characterization of Antimicrobial resistance-carrying genomes from waterbodies and sediments using PacBio long-read sequencing technology

SMP1: Characterization of antimicrobial resistance -carrying genomes from waterbodies and sediments using PacBio long-read sequencing technology 

The Leibniz Research Alliance has provided funding under the auspices of “Characterization of antimicrobial resistance (AMR)-carrying genomes from waterbodies and sediments using PacBio long-read sequencing technology”. This additional seed money will be used, as part of the project “Water as habitat and vector for AMR microbes (IPT6)”, to generate long-read metagenomes from the water column and sediments of freshwater ecosystems. Long-read sequencing is critical for establishing a link between antimicrobial (AMR) resistance genes and their carriers (bacterial and fungal species). Furthermore, investment on long-read sequencing may expand the knowledge regarding the specific vectors of resistance genes - such as plasmids or other mobile genetic elements- in aquatic ecosystems.

Start:    01.11.2021
End:      31.10.2024

Coordinating Institute

Coordination

  • Prof. Dr. Hans-Peter Grossart (IGB)

Partners

Projectteam 

  • Prof. Dr. Hans-Peter Grossart (IGB)
  • Prof. Dr. Alex Greenwood (IZW)
  • Prof. Dr. Ulrich Nübel (DSMZ)
  • M. Sc. Pau De Yebra Rodó (IGB)

 

 >     SMP2: Systematic global analysis of national action plans on antimicrobial resistance <     SMP2: Systematic global analysis of national action plans on
antimicrobial resistance

SMP2: Systematic global analysis of national action plans on antimicrobial resistance 

The majority of countries worldwide have now developed national action plans (NAPs) to control antimicrobial resistance (AMR). However, initial research indicates that the governance and implementation of many NAPs is severely delayed and incomplete.

In this project, together with the Global Health Governance Programme in Edinburgh, we are conducting a global governance analysis of all countries represented by a self-assessment survey in the global Tripartite Antimicrobial Resistance Database (TrACCS). For this, we are applying a governance framework to assess national AMR action plans from Anderson et al. (2019) to measure the global response to AMR.

Start:    01.05.2022
End:      31.07.2022

Coordinating Institute

Partners

Projectteam 

  • Prof. Dr. Wolfgang Hein (GIGA)
  • Dr. Anne Harant (GIGA)
  • Dr. Denise Dekker (BNITM)
  • Prof. Dr. Devi Sridhar (Global Health Governance Programme, University of Edinburgh)
  • Dr. Genevie Fernandes (Global Health Governance Programme, University of Edinburgh)
  • M. Sc. Jay Patel  (Global Health Governance Programme, University of Edinburgh)