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Magnitude of Potential Biases in a Simulated Case-Control Study of the Effectiveness of Influenza Vaccination
Abstract
Background Many influenza vaccine effectiveness estimates have been made using case-control methods. Although several forms of bias may distort estimates of vaccine effectiveness derived from case-control studies, there have been few attempts to quantify the magnitude of these biases. Methods We estimated the magnitude of potential biases in influenza vaccine effectiveness values derived from case-control studies from several factors, including bias from differential use of diagnostic testing based on influenza vaccine status, imperfect diagnostic test characteristics, and confounding. A decision tree model was used to simulate an influenza vaccine effectiveness case-control study in children. Using probability distributions, we varied the value of factors that influence vaccine effectiveness estimates, including diagnostic test characteristics, vaccine coverage, likelihood of receiving a diagnostic test for influenza, likelihood that a child hospitalized with acute respiratory infection had influenza, and others. Bias was measured as the difference between the effectiveness observed in the simulated case-control study and a true underlying effectiveness value. Results and conclusions We found an average difference between observed and true vaccine effectiveness of -11.9%. Observed vaccine effectiveness underestimated the true effectiveness in 88% of model iterations. Diagnostic test specificity exhibited the strongest association with observed vaccine effectiveness, followed…
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Waning of efficacy over time has been demonstrated with other vaccines.
“waning of efficacy over time has been demonstrated with other vaccines. 20”
From Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine (2021) · cites this paper as [20]
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Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine
Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., Diemert, D., Spector, S. A., Rouphael, N., Creech, C. B., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2035389 · Cited by 10,119
Metadata
- Authors
- Ferdinands, J. M., & Shay, D. K.
- Affiliations
- Centers for Disease Control and Prevention (US)
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-11-17
- Volume
- 54
- Issue
- 1
- Pages
- 25-32
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- OpenAlex
- W2112338048
- Cited by
- 35
- References
- 1
- Citations by year
- 2025: 1 · 2024: 1 · 2021: 3 · 2020: 3 · 2019: 1 · 2018: 5 · 2017: 3 · 2016: 2 · 2015: 2 · 2014: 4 · 2013: 8 · 2012: 2
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Infectious Diseases (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- influenza vaccine effectiveness, diagnostic specificity, confounding, children, acute respiratory infections, hospitalized children
- MeSH terms
- Adolescent, Antibodies, Viral, Child, Child, Preschool, Computer Simulation, Humans, Infant, Influenza, Human, Influenza Vaccines, Vaccination, Bias, Case-Control Studies
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