The impact of selection bias on vaccine effectiveness estimates from test-negative studies

• Published in: Vaccine Vol. 36; no. 5; pp. 751 - 757
• Main Authors: Jackson, Michael L., Phillips, C. Hallie, Benoit, Joyce, Kiniry, Erika, Madziwa, Lawrence, Nelson, Jennifer C., Jackson, Lisa A.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 29.01.2018; Elsevier Limited
• Subjects: Algorithms; Allergy and Immunology; Bias; Bias (Epidemiology); Clinical Studies as Topic; Communicable Disease Control - statistics & numerical data; Computer Simulation; Data processing; Effectiveness; Estimates; health services; Human; Humans; Immunization; Immunogenicity, Vaccine; Influenza; Influenza Vaccines - immunology; Influenza, Human - epidemiology; Influenza, Human - prevention & control; Methodology; Observational studies; Odds Ratio; pathogens; Patient Outcome Assessment; Population Surveillance; Public health; Respiratory diseases; risk; Selection Bias; Simulation; United States; Vaccination; Vaccine effectiveness; Vaccine efficacy; Vaccines; Vaccines - immunology; Viruses; United States > US; United States; Human; Methodology; Influenza; Vaccine effectiveness; Bias (Epidemiology)

Estimates of vaccine effectiveness (VE) from test-negative studies may be subject to selection bias. In the context of influenza VE, we used simulations to identify situations in which meaningful selection bias can occur. We also analyzed observational study data for evidence of selection bias. For...