In WP2, CONTAGIO will address key technical barriers to cohort interoperability identified in WP1, capitalising on the experience with data harmonisation and data sharing in ReCoDID and the Infectious Disease Data Observatory (IDDO13). We will collaborate with stakeholders within and outside of CONTAGIO to identify a minimal and extended set of variables needed to characterise syndromes of interest, including dengue and chikungunya viruses. These variables will be captured in Clinical Data Interchange Standards Consortium (CDISC) to ensure interoperability and will provide content to a web based CRF Builder. The CRF Builder combines flexibility with FAIR by allowing end users (cohorts) to create a customised eCRF from a suite of variables. Similarly, we will work with internal and external stakeholders to define a minimal set of metadata needed to describe related cohorts. Metadata will have broad agreement, will be FAIR, and machine readable to ensure FAIR convergence within related disease communities. WP2 will concentrate on the technical requirements to facilitate interoperability between cohort data sets. To this end, we will provide applied support for assisting cohorts in developing a clear workflow for data extraction, management, and harmonisation, particularly with respect to new data types such as etabolomics. Data on diagnostic tests has shown to be a source of  considerable heterogeneity in the last pandemic. We will develop a Bayesian approach to accounting for variance in arbovirus diagnostics to provide more accurate and interpretable diagnoses, in terms of probability of positivity14 that accounts for cross-reactivity and the use of diagnostic tools with various levels of accuracy across time, a persistent challenge for the research response to EIDs. and other sources of complex measurement error. These innovations in the analysis of EID diagnostic data will aid current and future pandemic response.