After nearly two years, the COVID-19 pandemic remains a public health emergency. Despite the employment of public health measures, such as restriction of movements and gatherings, personal protection, as well as massive vaccination campaigns, the coronavirus is still largely affecting the mortality and morbidity worldwide, including persisting symptoms after the infection. While the pandemic is evolving and countries are adapting their health systems to new phases of preventive measures, the research community is trying to fully elucidate the transmission and progression of the infection, as well as the most effective ways of treating and preventing new cases in preparation for any new waves, particularly due to new variants of SARS-CoV-2. This requires international harmonisation of data from different sources, so that a comparison can be made across health systems and patient characterization can be improved using a wider heterogeneity of information. 

The unCoVer (Unravelling data for rapid evidence based response to COVID-19) network aims to provide a research platform for the expert use of data obtained from the real world. By bringing together complementary data and medical and scientific expertise to address the still urgent questions regarding the determinants of the COVID-19 progression, the project hopes to inform more effective medical and public health strategies. 

The Horizon 2020-funded network includes 29 partners from 18 countries, who have been collecting COVID-19 patient information during the pandemic. Among these, LIH researchers from the Department of Precision Health and the Translational Medicine Operations Hub will contribute data from the Predi-COVID study. 

Predi-COVID was launched two years ago with the aim to identify important risk factors and biomarkers associated with COVID-19 severity and long-term health consequences of the disease in Luxembourg. Through it, the study contributed to elucidate why some patients infected by SARS-CoV-2 develop severe symptoms while others present only mild forms, which will ultimately lead to more personalized care recommendations. The study also included household members of Covid-19 positive participants to study the transmission of the virus in this high-risk population.

Real-world data such as those gathered in the unCoVer project are critical to understand and respond to the pandemic, and include, for example, patient characteristics and risk factors, or information on treatment efficacy. The unCoVer approach captures and collects these data in a standardised format, unifying otherwise scattered datasets whilst maintaining patient anonymity across countries.

The network will build ‘big data’ analysis tools, allowing clinicians, data scientists and epidemiologists, to collaboratively address questions including who is susceptible to serious disease. Whereas clinical trials often exclude the most vulnerable groups, unCoVer real-world data specifically includes these groups, therefore complementing and contrasting other studies.