Collider bias undermines our understanding of COVID-19 disease risk and severity

Abstract excerpt

Observational data on COVID-19 including hypothesised risk factors for infection and progression are accruing rapidly, often from non-random sampling such as hospital admissions, targeted testing or voluntary participation. Here, we highlight the challenge of interpreting observational evidence from such samples of the population, which may be affected by collider bias. We illustrate these issues using data from t...

Topics

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• Age Factors
• Aged
• Comorbidity
• COVID-19
• Genome-Wide Association Study
• Polymorphism, Single Nucleotide
• Severity of Illness Index
• Sex Factors

Identifiers and source

Literature Corpus work

7218112b-4711-509c-8e1c-e52135f66f45

DOI

10.1101/2020.05.04.20090506