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Multidrug-resistant organisms in the northern Dutch-German cross-border region

Epidemiology in clinical and environmental settings, detection methods, and infection control strategies
PhD ceremony:C. (Cansu) CimenWhen:February 04, 2026 Start:14:30Supervisors:prof. dr. A. (Andreas) Voss, prof. dr. A. HamprechtCo-supervisor:dr. M.S. (Matthijs) BerendsWhere:Academy building UGFaculty:Medical Sciences / UMCG
Multidrug-resistant organisms in the northern Dutch-German
cross-border region

Multidrug-resistant organisms in the northern Dutch-German cross-border region

Antimicrobial resistance (AMR) means that a microorganism cannot be killed by an antimicrobial agent. A microorganism can become resistant to multiple antimicrobial agents of different classes at the same time and is called a multidrug-resistant organism (MDRO).

MDROs are a global health problem because infections caused by MDROs can cause a high number of deaths worldwide due to limited and/or less effective treatment options, and MDROs can easily spread between persons, hospitals, and even countries. Both the emergence and spread of MDROs are influenced by various causal factors and control strategies, which makes the situation complex and necessities coordination between disciplines and across borders. Although there are international calls for collaboration, such initiatives remain limited in practice. Therefore, this thesis of Cansu Cimen aimed to study AMR in a European cross-border region using a collaborative approach, investigating epidemiology, environmental dissemination, detection methods, and infection prevention and control (IPC) strategies of MDROs. Knowledge of the prevalence of MDROs and accurate detection are necessary to support treatment decisions and to develop and update IPC policies. Accordingly, this thesis showed differences in the epidemiology and IPC guidelines for MDROs between neighbouring countries, demonstrated that surface water can act as a reservoir for MDROs, and reported the importance and variability of diagnostic methods for accurate detection of AMR.

In addition, a free web-based machine learning tool was introduced to support the prediction of AMR. Overall, this work illustrates the value of cross-border collaboration in addressing MDROs that do not know borders.

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