UNSTRUCTURED
Infectious disease (ID) cohorts are key to advancing public health surveillance, public policies and pandemic responses. Unfortunately, ID cohorts often lack funding to store and share clinical-epidemiological data (CE) and high-dimensional laboratory (HDL) data long-term, which is evident when the link between these data elements is not kept up to date. This becomes particularly apparent when smaller cohorts fail to successfully address the initial scientific objectives due to limited case numbers, which also limits the potential of pooling for these studies to monitor long-term cross-disease interactions within and across populations. To facilitate advancements in cross-population inference and reuse of cohort data, the European Commission (EC) and the Canadian Institutes of Health Research, Institute of Genetics (CIHR-IG) funded the ReCoDID (Reconciliation of Cohort Data for Infectious Diseases) Consortium to store and share harmonized and standardized CE and HDL data on a federated platform and also provide innovative statistical tools to conduct meta-analyses of the individual patient data. Here we describe the harmonization of CE data from nine arbovirus (arthropod-borne viruses) cohorts in Latin America, which serve as a starting point for the ReCoDID meta-cohort. CE data was retrospectively harmonized using Maelstrom’s methodology and standardized to Clinical Data Interchange Standards Consortium (CDISC).
This meta-cohort will facilitate various joint research projects, e.g., on immunological interactions between sequential flavivirus infections and for the evaluation of potential biomarkers for severe arboviral disease.