Evidence map›Paper›PMID 41884491›Full record

ReviewEClinicalMedicine2026

Considerations for epidemiological studies investigating emerging post-acute infection syndromes: Long Covid as a case study.

Daniel Ayoubkhani, Christina J Atchison, Amitava Banerjee, Chris Brightling, Melanie Calvert, Ian Diamond, Rosalind M Eggo, Paul Elliott, Rachael A Evans, Shamil Haroon and 11 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in EClinicalMedicine, 2026. 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
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

21 authors.

Daniel AyoubkhaniDiabetes Research Centre, University of Leicester, Leicester, UK.
Christina J AtchisonSchool of Public Health, Imperial College London, London, UK.
Amitava BanerjeeInstitute of Health Informatics, University College London, London, UK.
Chris BrightlingInstitute for Lung Health, National Institute for Health and Care Research Leicester Biomedical Research Centre, Department of Respiratory Science, University of Leicester, Leicester, UK.
Melanie CalvertCentre for Patient-Reported Outcomes Research, University of Birmingham, Birmingham, UK.
Ian DiamondFormer National Statistician, Government Statistical Service, Newport, UK.
Rosalind M EggoFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Paul ElliottSchool of Public Health, Imperial College London, London, UK.
Rachael A EvansInstitute for Lung Health, National Institute for Health and Care Research Leicester Biomedical Research Centre, Department of Respiratory Science, University of Leicester, Leicester, UK.
Shamil HaroonDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Emily HerrettFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Vahé NafilyanOffice for National Statistics, Newport, UK.
Lauren L O'MahoneyDiabetes Research Centre, University of Leicester, Leicester, UK.
Snehal M Pinto PereiraDepartment of Targeted Intervention, Division of Surgery and Interventional Science, University College London, London, UK.
Ash RoutenDiabetes Research Centre, University of Leicester, Leicester, UK.
Roz ShafranUniversity College London Great Ormond Street Institute of Child Health, London, UK.
Terence StephensonUniversity College London Great Ormond Street Institute of Child Health, London, UK.
Jonathan SterneBristol Medical School, University of Bristol, Bristol, UK.
Helen WardSchool of Public Health, Imperial College London, London, UK.
Francesco ZaccardiDiabetes Research Centre, University of Leicester, Leicester, UK.
Kamlesh KhuntiDiabetes Research Centre, University of Leicester, Leicester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidemiological research studies into Long Covid, currently defined by prolonged symptoms after SARS-CoV-2 infection, have reported widely varying prevalence estimates. As well as rapidly evolving scientific knowledge of Long Covid, these differences are partly driven by substantial methodological heterogeneity between studies, including the outcome definition of Long Covid; duration of follow-up; study design, period and population; sampling frame; data source; and the statistical techniques employed. Having a robust understanding of the prevalence of and risk factors for Long Covid is essential for informing treatment pathways, service provision and policy decisions. In preparation for the public health response to future epidemics and pandemics, this review outlines key epidemiological and statistical considerations and recommendations when designing studies of emerging post-acute infection syndromes, focussing on Long Covid as a case study.

Indexed as

EpidemiologyLong CovidMethodologyPAISPost-acute infection syndromesPost-COVID-19 condition

Identifiers

PMID41884491
PMCPMC13011065

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.