Understanding the first-wave of COVID-19 in Catalonia

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In our recent paper in Nature Communications we have described patient outcomes during the first-wave of COVID-19 in Catalonia. For this we used data from over 5.5 million people, around 80% of the population of Catalonia, drawn from the Information System for Research in Primary Care (SIDIAP) database. From this general population cohort, we identified more than 100,000 people who had an outpatient diagnosis of COVID-19, close to 17,000 who were hospitalised with COVID-19, and more than 5,000 who died after either being diagnosed or hospitalised with COVID-19 between 1st March and 6th May 2020. We saw that older age was the factor most strongly associated with worse outcomes (hospitalisations and deaths), with males and people with various comorbidities also at an increased risk.

Underpinning this study was the development of a dataset that provides a breadth of data capture rarely available in COVID-19 research, starting from a representative general population and with COVID-19 testing, outpatient diagnoses, hospitalisations, and deaths all captured over longitudinal follow-up. This is what allowed us to look at the full clinical pathways of people with COVID-19 during the first-wave of the pandemic in our recent study.

Bringing this dataset together, and generating reliable evidence from it, has occupied us since March 2020 when the COVID-19 pandemic arrived here in Catalonia. While such a project was not in any of our minds even just a month or two beforehand, we had been working on standardising SIDIAP data to a common data model for a number of years. In the last couple of years this has been aided by the support of the European Health Data & Evidence Network (EHDEN) project. Meanwhile, the value of using a common format had already been made clear with our work as part of the Observational Health Data Sciences and Informatics (OHDSI) community, where network studies can be run without the need to share patient-level data and with help from the wide range of open-source software that has been developed over the years.

This foundation meant that we didn´t need to reinvent the wheel when the COVID-19 pandemic hit, but rather could pivot to addressing the novel coronavirus using the approaches that had been developed and refined over the previous years. Because of this we were able to quickly use the incoming data on patients with COVID-19 in Catalonia, along with data from other partners from the OHDSI network, to provide an early description of the profiles of people being hospitalised with COVID-19.

As the COVID-19 pandemic continues, so does our work on bringing the requisite data together to understand the epidemiology of the disease. Sadly, COVID-19 diagnoses, hospitalisations, and related-deaths continue to accrue. And while the appearance of vaccinations in our data will herald a much brighter picture, research to understand the long-term direct and indirect effects of the COVID-19 pandemic will still be required and we plan to contribute to this task, building upon the work we have already done. 

Ed Burn

Postdoctoral researcher, IDIAPJGol/ University of Oxford

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