Co-RESPOND: a federated network of cohorts on mental health and adversity during the COVID-19 pandemic. Challenges, solutions and recommendations for retrospective data harmonization.

Background: The SARS-Cov-2 pandemic was associated with a substantial rise in trauma and stressor exposure. The Co-RESPOND consortium (part of the EU horizon 2020-funded RESPOND project) has been initiated to study the impact on mental health, using longitudinal data of separate international cohorts.Aims: The Co-RESPOND initiative aims to retrospectively harmonize mental health and resilience data of ongoing longitudinal cohort studies at the individual participant level; to create an interoperable network of cohorts within a secure environment; to manage these data along with harmonization products (e.g. transformation procedures and variable dictionaries) according to the FAIR principles; and to keep this network live in order to add new data waves or to be joined by new cohorts.Methods: Data were harmonized retrospectively according to the Maelstrom guidance. A federated data network (FDN) was created using the OBiBa software suite.Results: To date, Co-RESPOND consists of nine European cohorts and one global cohort, including 50,885 individual participants. This paper presents Co-RESPOND as a case study for retrospective harmonization of decentralized data where teams collected and transformed data without prior coordination, facing methodological as well as regulatory challenges. The process of this project is outlined in detail, so it could be applied by other researchers for future projects. Its outcomes and the resulting data harmonization products are presented.Conclusions and outlook: The harmonized data are now ready to be shared with external partners for analyses, and Co-RESPOND is open for more partners to join. Lessons learned throughout the project will be reported, and established classification standards will be recommended for use to generate data sets that are available for joint analyses from the start.Trial registration: ClinicalTrials.gov identifier: NCT04556565.