Open COVID-19 Dataset Aims To Accelerate Research and Improve Patient Outcomes
The DIVINE cohort makes data from more than 5,800 patients hospitalized with COVID-19 available to the scientific community.
The Biostatistics Unit at the Germans Trias i Pujol Research Institute (IGTP), in collaboration with researchers from several Catalan healthcare and research institutions, has published the DIVINE study database in Scientific Data, a Nature Portfolio journal. This journal specialises in the publication of datasets and promotes the accessibility, proper documentation and reusability of these resources by the scientific community.
The cohort includes clinical information from 5,813 patients hospitalised with COVID-19 during four waves of the pandemic, between March 2020 and August 2021, across five hospitals in the southern metropolitan area of Barcelona. The database contains information collected during hospitalisation and follow-up, including clinical characteristics, risk factors, treatments received and hospital outcomes.
The data have been published as an R package on CRAN, with an associated GitHub repository and a Zenodo record, facilitating access, traceability and reuse.
The dataset has been anonymised and can be used to study the progression of patients hospitalised with COVID-19, identify factors associated with clinical outcomes and validate predictive models. It can also serve as a teaching resource in fields such as biostatistics and epidemiology.
The cohort has already contributed to several studies on in-hospital mortality, long-term sequelae, patient stratification and the development of predictive models. With this publication, the authors are making the dataset available to the scientific community to facilitate its reuse in future studies and contribute to more open, reproducible and efficient research.
Cristian Tebé, head of the Biostatistics Unit at IGTP, highlights that "making clinical research data openly available is not only an act of transparency, but also an ethical commitment to science and society. It enables data reuse, the reproduction of analyses, the expansion of knowledge and the acceleration of research, while avoiding the unnecessary duplication of studies".
Reference: Pallarès N, Carmezim J, Rodríguez-Molinero A, et al. A multicenter COVID-19 database from four waves in the south metropolitan area of Barcelona, Catalonia. Sci Data. 2026. doi: 10.1038/s41597-026-07479-7
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