Fatigue, attention and memory disorders are three of the most common long-term symptoms after COVID-19. These post-COVID-19 consequences represent the greatest barriers to social participation. Therefore, it is crucial to understand the pathomechanisms underlying neurocognitive losses, to study the course of these losses and to find out how the social context can mitigate the negative consequences. Standardised neurocognitive tests have rarely been used to objectively measure symptoms. We know little about the long-term development and possible fluctuations in symptoms and about factors that can improve them. There is also a need for ecologically valid phenotyping with contextual factors to gain a pathomechanistic and individualised understanding of neurocognitive symptoms that can serve as a basis for future interventions. Our aim is to model the progression of neurocognitive symptoms after COVID-19 and make predictions based on demographic, immunological and neuronal markers. We also want to achieve detailed phenotyping and explore the role of social determinants and impact on daily life.

We are currently developing a digital application to record neurocognitive symptoms of post-COVID-19 and factors that could influence them using standardised neuropsychological tests. To develop this app, we asked those affected by post-COVID-19 how exactly their symptoms manifest themselves and what would be important to them in such an app.

The app is based on the specifications of the COFONI technology platform and uses openEHR data models so that we can integrate collected data into the COFONI technology platform. In a spin-off study, the application will be used to record the symptoms of post-COVID-19 patients over a period of several weeks and thus contribute to a more detailed phenotyping of post-COVID courses.

In addition, we calculate prognostic models that describe the course of post-COVID symptoms over a longer period of time and identify different phenotypes. In doing so, we investigate which markers contribute to differences between patients and which can be considered as possible protective factors or starting points for interventions. We use different longitudinal datasets to develop these models (e.g. NAPKON database, UK Biobank, specially collected datasets from UOL and MHH) and then test them (e.g. SveDem cohort in a co-operation with the Karolinska Institute).

Funded as part of the COVID-19 Research Network Lower Saxony (COFONI) https://www.umg.eu/forschung/corona/cofoni/ by the Lower Saxony Ministry of Science and Culture (MWK)

Key area 5: Interdisciplinary research into the long-term consequences of the SARS-CoV-2 pandemic

Click here for our project page of the COVID-19 Research Network Lower Saxony (COFONI):

https://www.umg.eu/forschung/corona/cofoni/sb-5/projekt-7lzf23/

• University of Oldenburg (UOL)
• Hanover Medical School (MHH)
• Rehabilitation Centre Oldenburg

• Prof. Dr Mandy Roheger
• Prof Dr Antje Wulff

• Prof Dr Andrea Hildebrandt
• Prof Dr med Katrin Weissenborn
• Prof Dr Gundula Zoch
• Dr Meike Dirks
• Dr Ann-Katrin Hennemann, M.Sc.
• Ann-Kathrin Knak, M.Sc.
• Jella Voelter, M.Sc.

Within the project, it is very important to us to communicate our results to the general public. We therefore actively participate in various science communication events, where we give presentations and run information stands, e.g. the "Uni in der Stadt" campaign organised by The Smart House Oldenburg.