NAPKON - National Pandemic Cohort Network

National Pandemic Cohort Network (NAPKON) is a stand-alone project within NUM. It was brought together from several individual project applications for cohort structures. Among others, the following projects were considered: COVIDOM, LEOSS.deep, and Pa-COVID-19. The main goal of NAPKON is to establish a harmonized, extensible, and interoperable network, focusing on two different approaches. First, the study of COVID-19 and its consequences, and second, the establishment of structures and infrastructures for possible future pandemics. In the context of COVID-19 research, NAPKON comprises three cohort platforms: the cross-sector platform (SÜP) focuses on all COVID-19 patients from different facilities and institutions, the high-resolution platform (HAP) focuses on inpatients and severe disease progression from all German university hospitals, and the population-based platform (POP) is based on a one-year study program and focuses on follow-up and patient-reported outcomes.   In addition, to the three cohorts, four infrastructure cores have been established. All four cores are responsible for additional tasks beyond the three cohorts. The Interaction Core focuses on collaboration among the various groups within NAPKON. The Biospecimen Core is for quality-assured collection and storage of biospecimens of all types. The Epidemiology Core is responsible for the quality-assured collection and analysis of data generated in NAPKON, and the Integration Core coordinates the integration of inventory data from previous studies into NAPKON.    

  

The GECCO core data set is an important component of NAPKON. The project will develop additional modules based on the GECCO core dataset. The development of additional modules is based on different perspectives such as pediatrics, cardiology, and vaccination. Another focus is the development of GECCOplus. The GECCOplus dataset is the intersection of all three cohort datasets. Various standards and terminologies such as LOINC, SNOMED -CT, ATC, and others are used as part of interoperability.