NTNU COVID-19 Modelling Taskforce - NTNU Biotechnology
NTNU COVID-19 Modelling Taskforce
NTNU COVID-19 Modelling Taskforce
The NTNU COVID-19 Modelling Taskforce has developed high-resolution modeling tools capable of identifying
- An efficient and systematic testing regime that can reduce number of infections.
- A more efficient vaccination system allowing for faster herd immunity than vaccinating by age.
- Optimal ways of lifting restrictions while ensuring the epidemic is limited,
- Control measures differentiating between regions and municipalities.
Large-scale testing, or ‘screening testing', has proven to be important to deal with the covid pandemic. We have argued that saliva testing is a practical and easy way to perform simple testing and large-scale testing. After completing a pilot study among 140 students in Trondheim, saliva testing is now available in Trondheim as the only city in Norway.
The taskforce has worked closely to connect data analysis with control theory and epidemiological modeling. This has not yet led to results widely communicated.
The central part of our platform is a high-resolution epidemiological network model that relies on detailed demographic and statistical data that is interfaced with advanced nonlinear optimal control methodology. This is a highly transdisciplinary undertaking, combining critical knowledge from the Life Sciences, Mathematical Sciences, Engineering and Economics.
The diagram below outlines how we perceive our role as provider of decision support information to Norwegian governmental agencies and authorities.
The dotted black lines reflect that we use the latest official Norwegian policies and reports as a base-line for our work. However, the primary use of the modelling framework is to present optimal, but still feasibility-constrained, policy regimes that follow from a set of alternative control objectives scenarios. The construction of these scenarios are guided by results from a Norwegian macroeconomic model.
Team leaders of the four main pillars of the modelling framework
- NTNU Data analysis: Professor Ingelin Steinsland
- NTNU Model predictive control: Professor Thor I. Fossen
- NTNU Epidemiological network model: Professor Eivind Almaas
- NTNU Economic analysis of policy regimes: Professor Asgeir Tomasgard
If you have questions about the NTNU COVID-19 Modelling Taskforce activity beyond what you find on this website, please contact:
Trygve Brautaset, Email: firstname.lastname@example.org, Phone: +47 98 28 39 77
NTNU COVID-19 ingress
This website is the primary outreach channel for NTNU’s modelling taskforce dedicated to the understanding and control of the COVID-19 dynamics in Norway. NTNU's motivation for setting up this taskforce is to generate valuable insights that can support the Norwegian authorities in their endeavour to manage the pandemic as safely and effectively as possible.
The justification for the way we approach the COVID-19 predicament is that the COVID-19 dynamics and our attempts to contain and eradicate it, constitute a very complex system with numerous negative and positive feedback loops. Systems such as these are very difficult to analyse and control in an optimal way, unless one makes use of the very same theoretical tools that much of the technology underlying modern civilization is based on.
This work is funded by NTNU as part of its societal responsibility.
Epidemiological network model
Trøndelag Health Study data (The HUNT Study)
Central Norway Regional Health Authority (Helse Midt-Norge)
St. Olavs Hospital