Good health is essential for a quality of life, whether for humans or. animals. Understanding the mechanisms of what keeps us healthy, requires knowledge and research. NR plays a significant role in many interdisciplinary, collaborative projects, providing statistical expertise to promote better health and well-being.

Statistical applications and modelling in health 

A lot of data is collected in all areas of health from municipal services, specialist health services, health trusts and national bodies. NR is working to analyse and model this data to extract the important information. 

Our expertise covers the full range of statistical methods, from common regression models to complex Bayesian hierarchical modelling. In close collaboration with partners, mechanistic models based on physical, chemical or biological knowledge are often combined with computer-driven, stochastic models. A good research project will often include participants with different backgrounds, and we have extensive experience in collaborating with doctors, biologists, pharmacologists, veterinarians and others.

Successful interdisciplinary collaborations are beneficial to society at large. A recent example is our collaboration with the Norwegian Institute of Public Health (NIPH) during the coronavirus pandemic. Here, we modelled domestic COVID-19 transmission in order to understand how and where the spread of infection was taking place. The models were based on senior researcher Solveig Engebretsen’s doctoral thesis which looked at how network science how network science could be used to understand and predict various public health phenomena.

One of our longest collaborations is with the Department of Pharmacology and Mathematics at the University of Oslo (UiO), where we are examining drug use in connection with Parkinson’s disease. 

In general, NR has extensive experience in registry data research also in connection with, among other things, cancer drugs, anti-anxiety drugs and sleeping pills, antipsychotic drugs, cholesterol-lowering drugs, anticoagulants and drugs for heartburn, stomach ulcers and ulcers in the esophagus (proton pump inhibitors). 


NR has worked with genomic data for many years in collaboration with health trusts and universities. Some examples are: 

NR participates in the core facility for bioinformatics at the University of Oslo, and offers statistical advice and analysis of genomic data. 

NR has extensive experience with analyses of, for example, micro-RNA, DNA methylation, RNA sequences, SNPs and mRNA expression data. NR also participates in the research project Id-Lung at the UiT The Arctic University of Norway, which uses multiomic data to identify biomarkers for metastatic lung cancer. 

Medical image analysis 

NR works with many different types of images in health; ultrasound, X-ray and MRI. For all types of images, NR works with detection, characterisation and recognition of different types of objects and phenomena in the images. 

Digital inclusion in health 

Much of the dialogue with patients is digital. Then the computer systems must be designed so that as many patients as possible master the digital dialogue. NR has extensive experience in the area and works with issues from the primary health service to directorates. 

Medical sensors 

There is a significant increase in the use of medical sensors in many types of medical treatment and monitoring. NR has worked with a number of issues in this area including  privacy and secure transmission and data collection. 

Health involves these research areas