ArticleInternational journal of epidemiology2023
Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.
Article in International journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of post-COVID condition in Nordic population-based registry studies.Nature communications · 2025Pooled it
- A Systematic Review of Nirmatrelvir/Ritonavir and Molnupiravir for the Treatment of Coronavirus Disease 2019.Open forum infectious diseases · 2024Trial
- HLA Class I and II Variants as Potential Determinants of Clinical Severity and Mortality in Patients with COVID-19: A Prospective Study from Saudi Arabia.Biomedicines · 2026Article
- Long COVID Persistence and Surveillance Gaps Across 58 US Hospitals.JAMA network open · 2026Article
- Long-Term Impact of EGUIDE Training on Facility-Wide Guideline Adherence Rate in Schizophrenia and Major Depressive Disorder-A Methodological Reflection.Neuropsychopharmacology reports · 2026Article
- Selection Biases in Perinatal Research: A Comparison of Inverse Probability Weighting, Instrumental Variable and Sibling-Comparison Design.Paediatric and perinatal epidemiology · 2026Article
- Determinants of ADHD Health Literacy and Public Awareness of Child-Friendly City Policies in Wenzhou: A Cross-Sectional Survey.Neuropsychiatric disease and treatment · 2026Article
- Social isolation, loneliness, and positive affect before and during the COVID-19 pandemic in very old adults living in Germany: a quasi-experimental multi-sample study.BMC geriatrics · 2025Article
- Neighborhood environmental vulnerability factors strongly drove COVID-19 fatality and excess all-cause mortality in New York City, while long-term air pollutant associations were weak and varied.The Science of the total environment · 2025Article
- Strategies for Creating Robust Patient Groups to Study Diverse Conditions with Electronic Health Records.Annual review of biomedical data science · 2025Review
- Household-income trajectories and mental health inequalities in Germany before, during, and after the COVID-19 pandemic: a quasi-experimental panel study.International journal for equity in health · 2025Article
- Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review.Journal of medical Internet research · 2025Review
- Abdominal obesity and osteoarthritis risk: evaluating the association of lipid accumulation product, body roundness index, and waist triglyceride index with osteoarthritis in U.S. adults.Frontiers in nutrition · 2025Article
- Cardiac Arrhythmias and Autonomic Dysfunction Associated With COVID-19: A Scientific Statement From the American Heart Association.Circulation · 2024Review
- Accounting for bias due to outcome data missing not at random: comparison and illustration of two approaches to probabilistic bias analysis: a simulation study.BMC medical research methodology · 2024Article
- Longitudinal investigation of a single variant SARS-CoV-2-outbreak in the immunologically naïve population of Ulvik, Norway.BMC infectious diseases · 2024Article
- Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK.BMC medicine · 2024Article
- Symptom burden, coagulopathy and heart disease after acute SARS-CoV-2 infection in primary practice.Scientific reports · 2024Observational
- Air Pollution in Relation to COVID-19 Morbidity and Mortality: A Large Population-Based Cohort Study in Catalonia, Spain (COVAIR-CAT).Research report (Health Effects Institute) · 2024Article
- Analysis of Missingness Scenarios for Observational Health Data.Journal of personalized medicine · 2024Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundNon-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis.
methodsWe tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19.
resultsIn both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios.
conclusionsAnalyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.
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