Data dictionary for harmonised dataset of key clinical-epidemiological variables from EC-funded COVID-19 (cohort) studies that will share data through the COVID-19 Datahubs

Task 82 Reconciliation of clinicalepidemiological dataLead UKHD other beneficiaries and partners involved UCD RIMUHC MaelstromWithn Task 82 we will harness the methodology and synergies developed in ReCoDiD WP3 to apply best practice for the harmonisation of clinicalepidemiological data and advance the state of the art for the harmonisation of participantlevel clinical epidemiological data in the research response to epidemics Harmonisation efforts will focus on the ECfunded COVID19 cohort projects that are collecting primary clinicalepidemiological data but the methodology will be applicable to a broad spectrum of COVID19focused human subject studies ReCoDid WP3 focuses on applying best practice when available and developing new methods when best practice is insufficient or has not been specified for crosscohort prospective and retrospective harmonisation and analysis In WP3 we have focused on prospective Arbovirus data sets available to the investigators in order to test the methodology Task 82 will leverage this expertise to rapidly extend the findings from harmonisation and methodological best practice developed in the context of Arbovirus Zika and dengue virus focused cohorts to COVID19focused longitudinal studies Conducting the actual work of reconciliation of data dictionaries and data harmonisation will involve a substantial additional workload for the existing teams To conduct the work as rapidly as possible while maintaining adherence to the highest standards for the documentation of harmonisation and the quality of the harmonised dataset we will work closely with the larger interconsortium harmonisation working group that was convened by the ReCoDID coordinator to ensure crossfertilisation of ideas from different types of experts and EC Horizon 2020funded projects with diverse fociAs mentioned we will collaborate closely with a partner from Canada Maelstrom Research associated with McGill University to which we were introduced through the EUCAN crossconsortional working group The Maelstrom team brings essential experience to guide the process of applying best practice to the documentation of complex harmonisation decisions Our preexisting work to launch and manage the crossConsortia harmonisation working group and our close ties to Maelstrom will enable us to rapidly assemble the diverse expertise and manage the crossnational collaborative work force necessary to achieve the goals of this projectWell characterised metadata is a fundamental component of FAIRification of existing data Detailed study metadata will be collected from studies that have agreed to share participantlevel data to the COVID19 data hubs Metadata will collect specific information on COVID19 diagnostics and how the diagnostics varied over time and the detailed metadata survey will be informed by the laboratory and field data collection protocols from studies that will contribute data to the ReCoDID platform and COVID19 Data Hubs The metadata survey will produce a detailed dataset that is specific to studies that share participantlevel data to the ReCoDID Platform and COVDI19 Data hubs Agreed outputs of harmonisation at the level of cohort metadata will be captured into the cohort browser as additional searchable annotations to allow discovery across cohorts