Data streams and mathematical modelling pipelines to support preparedness and decision making for COVID-19 and future pandemics (NordicMathCovid)

The project participants comprise epidemiologists, statisticians, mathematicians, and computer scientists, and will involve several participants from each of the three national public health institutes, with the directors of the institutes contributing as members of the Scientific Advisory Board of the project.

The aim of the project is to use clinical health data combined with real-time data streams representing social activity and human mobility, together with advanced mathematical modelling and computational methods to address several of the most urgent questions for COVID-19 and future pandemics:

  • What effects do community structure, individual heterogeneities, and spatial mobility have on reproduction numbers, community immunity, and the efficacy of different preventive measures?
  • How can real-time data streams of social activity and human mobility combined with clinical health data aid in making more accurate predictions and more informed control decisions related to structurally and geographically targeted nonpharmaceutical interventions?
  • How can Nordic health data and novel data streams of relevance for the ongoing COVID-19 and future pandemics be shared and published in a way that allows for better analyses without compromising data privacy of the individuals?

The project will develop methods, tools, and operational procedures for implementing cross-Nordic interoperable health data pipelines, novel methodology published in international scientific journals, and support the national public health institutes in their aim to keep disease spreading low without causing too high burden on Nordic societies.


Maria Nilsson

Maria Nilsson

Special Adviser