We will establish an internationally unique multi-country database network with data from healthcare registers in Denmark, Norway, Sweden and Scotland with the purpose of conducting epidemiological studies on Covid-19.
The access to population-based data covering 25 mill. people will provide opportunities to study and thoroughly characterise disease course in individuals and evaluate the impact of the pandemic on healthcare. We will also evaluate differences across countries and the possible influence of different policies.
Focus will be on risk factors for severe Covid-19 (disease leading to hospitalisation, intensive care or fatal outcome), identifying vulnerable populations and characterising the disease course, also pertaining to long term sequelae among survivors of severe Covid-19. Additionally, we will investigate collateral effects of the pandemic on healthcare and drug utilisation in the general population to assess secondary effects on public health.
In our analyses we will combine data science approaches and state-of-the-art epidemiological methods. We will apply machine learning for hypothesis generation and test findings in studies using more conventional epidemiological methods.
WP1 Common data model (CDM) and analytics (Prof. Andersen)
WP2 Risk factors and machine learning (Ass. Prof. Sessa)
WP3 Vulnerable populations and Covid-19 outcomes (Prof. Nordeng)
WP4 Healthcare and drug utilisation (Prof. Wettermark)
The project is a 2-year project funded by Nordforsk.