ArticleNature communications2020
Collider bias undermines our understanding of COVID-19 disease risk and severity.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 504 papers, 6 of them syntheses that pooled 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.
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.
Generalizable Prognostic Models for Patient-Centered Decisions in COVID-19
Tobacco Use and Incidence of SARS-CoV-2 Infection in the Finnish General Population
Who cites it
504 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- STROBE-causal machine learning for the human microbiome: systematic review on methodological innovations and validation frameworks.Frontiers in microbiology · 2026Pooled it
- A systematic review and meta-analysis of the impact of vaccination on prevention of long COVID.Nature communications · 2025Pooled it
- Biases and limitations in observational studies of Long COVID prevalence and risk factors: A rapid systematic umbrella review.PloS one · 2024Pooled it
- Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.PLoS genetics · 2023Pooled it
- Repurposed drug studies on the primary prevention of SARS-CoV-2 infection during the pandemic: systematic review and meta-analysis.BMJ open respiratory research · 2023Pooled it
- Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis.The Science of the total environment · 2023Pooled it
- The validity of test-negative design for assessment of typhoid conjugate vaccine protection: comparison of estimates by different study designs using data from a cluster-randomised controlled trial.The Lancet. Global health · 2025Trial
- Our Future Health and the next generation of population medicine.Nature medicine · 2026Article
- Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health.Nature medicine · 2026Article
- AI Cautionary Guide: Pitfalls and Strategies for the Use of Machine Learning in Medical Research.Clinical pharmacology and therapeutics · 2026Review
- Using causal frameworks to reduce bias in observational TB research: a comparison of model-building approaches.IJTLD open · 2026Article
- Investigating the repurposing potential of immune checkpoint inhibition for cancer treatment using Mendelian randomisation.Research square · 2026Article
- The burden of antimicrobial-resistant bacterial infections: a causal perspective.Nature communications · 2026Review
- Cross-Sectional Studies: Strengths, Limitations, and Methodological Considerations.Journal of periodontal research · 2026Review
- Outcomes and Predictors of Mortality in Perforated Versus Non-Perforated Peptic Ulcer Disease: A U.S. Nationwide Propensity-Matched Analysis, 2016-2021.Journal of clinical medicine · 2026Article
- Socio-Demographic Inequalities in COVID-19 Health Care Access and Experiences in the United Kingdom: Intersectional and Mixed-Methods Analyses of Open and Closed Questions in a Prospective Cohort Study.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- From case counts to probability sampling: Simulation insights into pandemic surveillance.Public health in practice (Oxford, England) · 2026Article
- UK Biobank at 20 - a growing, global resource for dementia research.Nature reviews. Neurology · 2026Review
- Detecting dataset bias in medical AI using a generalized and modality agnostic auditing approach.NPJ digital medicine · 2026Article
- Polygenic risk score and 20-year prostate cancer-specific mortality and survival.Communications medicine · 2026Article
444 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.
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Registered trials
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.