Abstract
Safe and effective vaccines are crucial for the control of Covid-19 and to protect individuals at higher risk of severe disease. The test-negative design is a popular option for evaluating the effectiveness of Covid-19 vaccines. However, the findings could be biased by several factors, including imperfect sensitivity and/or specificity of the test used for diagnosing the SARS-Cov-2 infection. We propose a simple Bayesian modeling approach for estimating vaccine effectiveness that is robust even when the diagnostic test is imperfect. We use simulation studies to demonstrate the robustness of our method to misclassification bias and illustrate the utility of our approach using real-world examples.
Original language | English |
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Article number | 55 |
Journal | BMC Medical Research Methodology |
Volume | 23 |
ISSN | 1471-2288 |
DOIs | |
Publication status | Published - 2023 |
Bibliographical note
Funding Information:This work was funded by COST Action CA18208: HARMONY-Novel tools for test evaluation and disease prevalence estimation https://harmony-net.eu .
Publisher Copyright:
© 2023, The Author(s).
Keywords
- Covid-19
- RT-PCR
- Sensitivity
- Specificity
- Test-negative design