The rapid generation of heterogeneous biomedical research data during the SARS-CoV-2 pandemic demonstrated some of the challenges integrating multi-modal datasets required for rapid-response decision-making. In particular, it highlighted the need for research data systems capable of harmonising longitudinal clinical, serological, and experimental assay data to support viral and immune surveillance.

In response, we developed a modular data infrastructure that underpins our ongoing virology research for the UCLH Crick Legacy study (REC20/HRA/4717). This observational cohort began in January 2021 to characterise SARS-CoV-2 infection- and vaccine-induced immune responses. The infrastructure supports the ingestion and integration of participant-level data spanning serological measurements, clinical metadata, recorded vaccination, and experimental assay outputs conducted repeatedly over years.

Our data model enforces harmonisation across modalities, enabling linkage of longitudinal records at the participant and sample levels. Time-indexing and data alignment is performed using our publicly-available R package, chronogram. Data integration workflows standardise assay outputs and clinical variables into a unified schema, supporting version-controlled updates as new data are acquired.

Our system provides structured data outputs to support downstream analyses that investigate the ongoing effects of the pandemic on immunity, reducing the gap between hypothesis generation and computational implementation. As a result, it has supported analyses within the Legacy study and collaborating consortia, including seasonal vaccine monitoring and real-time estimates of immune response against SARS-CoV-2 variants.

Beyond Legacy, this research infrastructure continues to develop with pandemic preparedness in mind, and presents a framework for developing modular data architectures that can support future infectious disease surveillance and response.

Co-authors: David Greenwood, Mary Y Wu, David Lv Bauer, Edward J Carr, Emma Wall