A multicenter COVID-19 database from four waves in the south metropolitan area of Barcelona, Catalonia, 2026, Pallarès et al.

Chandelier

Senior Member (Voting Rights)
A multicenter COVID-19 database from four waves in the south metropolitan area of Barcelona, Catalonia

Pallarès, N.; Carmezim, J.; Rodríguez-Molinero, A.; Coloma, A.; Izquierdo, E.; Díaz-Brito, V.; Videla, S.; Carratalà, J.; Gómez-Melis, G.; Tebé, C.

Abstract​

The COVID-19 pandemic has been characterized by a series of epidemiological waves, each defined by distinct viral variants and shifting transmission dynamics.
Examining these waves is essential for understanding temporal changes in case incidence, hospitalization rates, mortality patterns, and healthcare system capacity.
In this work, we present a database from a multicenter COVID-19 study including data of 5813 patients from four waves of the pandemic in the south metropolitan area of Barcelona.
The database contains information collected at hospital admission and during patient follow-up while in hospital.
Data were prospectively recorded from the patients’ medical records.
The database includes information on demographic characteristics, comorbidities, and clinical signs and symptoms at admission, as well as detailed data on clinical management and treatments administered during hospitalisation across four pandemic waves.
The database has been made publicly available to support reproducible research and to enable its reuse in secondary analyses and predictive model validation, and for use as a teaching resource.


Web | DOI | Scientific Data
 

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.
 
Back
Top Bottom