Evidence map›Paper›PMID 40145004›Full record

ArticleFrontiers in public health2025

Development of the ECHOES national dataset: a resource for monitoring post-acute and long-term COVID-19 health outcomes in England.

Hester Allen, Katie Hassell, Christopher Rawlinson, Owen Pullen, Colin Campbell, Annika M Jödicke, Martí Català, Albert Prats-Uribe, Gavin Dabrera, Daniel Prieto-Alhambra and 1 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Hester AllenImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Katie HassellImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Christopher RawlinsonImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Owen PullenImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Colin CampbellImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Annika M JödickeHealth Data Sciences, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, United Kingdom.
Martí CatalàHealth Data Sciences, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, United Kingdom.
Albert Prats-UribeHealth Data Sciences, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, United Kingdom.
Gavin DabreraImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.
Daniel Prieto-AlhambraHealth Data Sciences, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, United Kingdom.
Ines Campos-MatosImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Electronic health records can be used to understand the diverse presentation of post-acute and long-term health outcomes following COVID-19 infection. In England, the UK Health Security Agency, in collaboration with the University of Oxford, has created the Evaluation of post-acute COVID-19 Health Outcomes (ECHOES) dataset to monitor how an initial SARS-CoV-2 infection episode is associated with changes in the risk of health outcomes that are recorded in routinely collected health data. Methods: The ECHOES dataset is a national-level dataset combining national-level surveillance, administrative, and healthcare data. Entity resolution and data linkage methods are used to create a cohort of individuals who have tested positive and negative for SARS-CoV-2 in England throughout the COVID-19 pandemic, alongside information on a range of health outcomes, including diagnosed clinical conditions, mortality, and risk factor information. Results: The dataset contains comprehensive COVID-19 testing data and demographic, socio-economic, and health-related information for 44 million individuals who tested for SARS-CoV-2 between March 2020 and April 2022, representing 15,720,286 individuals who tested positive and 42,351,016 individuals who tested negative. Discussion: With the application of epidemiological and statistical methods, this dataset allows a range of clinical outcomes to be investigated, including pre-specified health conditions and mortality. Furthermore, understanding potential determinants of health outcomes can be gained, including pre-existing health conditions, acute disease characteristics, SARS-CoV-2 vaccination status, and genomic variants.

Indexed as

COVID-19Datasets as TopicElectronic Health RecordsAdolescentAdultAgedEnglandFemaleHumansMaleMiddle AgedRisk FactorsSARS-CoV-2COVID-19data linkageelectronic health datahealth outcomespost-acute COVID-19

Identifiers

PMID40145004
PMCPMC11936881

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.