News Release

New Western Norway initiative to combat antimicrobial resistance

Business Announcement

The University of Bergen


image: The team at The Centre for Antimicrobial Resistance in Western Norway (CAMRIA). view more 

Credit: Jørgen Barth/University of Bergen

Research questions to be studied are how and why resistance develops and spreads, and how healthcare personnel, politicians and the general public can be encouraged to reduce unnecessary use of antibiotic

The new centre for antimicrobial resistance in Western Norway will stimulate interdisciplinary research collaboration, to link knowledge and methods from medicine with the social sciences, informatics and mathematics. The research centre has therefore been named CAMRIA – Combating Anti-Microbial Resistance with Interdisciplinary Approaches.

– Three projects will now be initiated with funding from the Trond Mohn Foundation, says Nina Langeland, head of the centre and professor of infectious diseases at the University of Bergen (UiB). The Trond Mohn Foundation is supporting the initiative, which will run until 2026, with NOK 25.7 million, and the host institutions will together contribute with an equivalent amount.

– Funding research that can help to limit the risk of antimicrobial resistance is probably our most important contribution,’ says CEO of the Trond Mohn Foundation Sveinung Hole. ‘The national programme against antimicrobial resistance is our biggest ever investment. CAMRIA complements this investment, he adds.

How can attitudes and behaviour be changed?
One of the three research projects at CAMRIA is exploring the extent to which healthcare personnel and the general public understand the risk posed by the lack of effective antibiotics for combating in part life-threatening infections. This work will form the basis for better and more efficient communication about this risk. Ingrid Smith, senior consultant, and specialist in infectious diseases at Haukeland University Hospital, is head of the project:

– Risk communication and understanding among the general public and healthcare personnel – necessary knowledge for developing new plans and interventions.The COVID-19 pandemic has been described as an ‘infodemic’, or an information pandemic, which has contributed to changing people’s behaviour. In a short space of time, people have understood the necessity of infection control measures such as washing hands, physical distancing and using face masks. Antimicrobial resistance is also a pandemic, but it has not led to similar behavioural changes in the form of infection control measures and more appropriate use of antibiotics,’ she says and adds:

– We therefore need to learn more about how healthcare personnel and the general public understand the risk and use this knowledge to bring about necessary changes in behaviour. The goal is to investigate how antimicrobial resistance is presented in the media and how attitudes and actions related to the problem are formed. 

The project is designed to include interviews with both healthcare personnel and the public, the latter through the Norwegian citizens panel which will be led by Professor Anne Lise Fimreite, UiB. Professor Jens E. Kjeldsen, UiB will lead the work on how antimicrobial resistance is presented in the media. In addition to the researchers in Bergen, specialists in infectious diseases from Imperial College London will be involved in the project.

Using machine learning to monitor and trace resistant genes
Antimicrobial resistance (AMR) has increased together with the increase in use of medicines such as antibiotics in the healthcare sector and in other industries. A large percentage of antimicrobial resistant genes (ARG) found in humans originate in nature and environments outside hospitals. Few studies have been carried out on these ARG reservoirs, despite the transfer of resistant genes from the environment playing an important role in the development of multi-resistant bacteria. Monitoring of AMR is further challenged by not knowing which bacteria are the source of ARGs, making it difficult to trace AMR across environments.

These challenges form the basis for the project ‘Surveillance and metagenomic tracking of antimicrobial resistance genes in environmental and clinical samples using machine learning approaches’. The project is managed by researcher Randi Jacobsen Bertelsen from the Department of Clinical Science 2 at UiB.

HyperEvol – predicting the development of antimicrobial resistance
In the third project, mathematicians from UiB will join forces with medical researchers from Bergen and Stavanger to develop methods that can predict the spread of antimicrobial resistance. Researchers from the Institute of Microbiology and Infection at the University of Birmingham will also participate in the project-

– To understand which factors lead to the development and spread of AMR, there is a pressing need for new approaches that can identify development processes in the body from a real dataset. This will enable us to use the large and increasing quantity of clinical data to develop models that are suitable for this purpose,’ says project leader Iain Johnston, who is professor of mathematics at the Department of Mathematics at UiB.

Important in the specialist health service
Haukeland University Hospital is the chair of the National Centre for Antibiotic Use in Hospitals (KAS).

– Knowledge sharing that can limit the use of antibiotics in hospitals is extremely important to combat resistance. The research projects taking place at CAMRIA will contribute to that end, says CEO of Helse Bergen health trust Eivind Hansen.

Rector Margareth Hagen of UiB emphasises the importance of the new research centre taking an interdisciplinary approach to the challenges antimicrobial resistance represents.

– We look forward to following the projects’ development and using the new knowledge they will produce, Hagen concludes.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.