Finished project

This project is completed. Enabling Technology lasted from 2011 to 2023.

NTNU COVID-19 Modelling Taskforce

NTNU Biotechnology

NTNU COVID-19 Modelling Taskforce

Two researchers demonstrating the spit sample test. Photo

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.
 


Corona virus close-up illustration

Methods

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.

Role as provider with observations chart

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.

Please visit this page for further documentation of our work

Team leaders of the four main pillars of the modelling framework

If you have questions about the NTNU COVID-19 Modelling Taskforce activity beyond what you find on this website, please contact:

Trygve Brautaset, Email: trygve.brautaset@ntnu.no, Phone: +47 98 28 39 77

NTNU COVID-19 ingress

corona virus illustrtaion

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.

 

Taskforce members

Taskforce members

Epidemiological network model

Eivind Almaas
André Voigt
Martina Hall
Nikolay Martyushenko
Emil Karlsen
Kristen Nyhamar
Signe Sævareid
Pål Røynestad

Model predictive

Thor I. Fossen
Erlend M. Lervik Coates
Pål Holthe Mathisen
Morten Hovd
Edmund Førland Brekke

Data analysis

Ingelin Steinsland
Harald Martens
Adil Rasheed
Geir-Arne Fuglstad
Andrea I. Riebler
Johan Håkon Bjørngaard
Pål R. Romundstad

Economic analysis

Asgeir Tomasgard
Paolo Pisciella
Simon Risanger
Steffen J. Bakker

HUNT Cloud

Oddgeir Lingaas Holmen
Matus Kosut
Sandor Zeestraten
Tom-Erik Røberg
Qussay Ghazeia

Virological expertise

Andreas Christensen

Trøndelag Health Study data (The HUNT Study)

Steinar Krokstad
Signe Opdahl
Erik R. Sund

Assisting resources

Central Norway Regional Health Authority (Helse Midt-Norge)

Nina Hagesæther

St. Olavs Hospital

Andreas Asheim

Aker Scholarship

Bjørn Blindheim