Why the study?
Test-negative designs evaluate vaccine effectiveness but remain subject to residual confounding and collider stratification bias from healthcare seeking behavior, occupation, or prior infection.
Population
Individuals with data from the University of Michigan Health System
Comparison
COVID-19 vaccination vs unvaccinated
Design
Methodological paper with simulations and empirical application using a test-negative design
Key result
A novel double negative control inference approach was developed to account for hidden biases in test-negative design studies and applied to estimate COVID-19 vaccine effectiveness.
Authors
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May refine bias adjustment in test-negative vaccine studies; leaves open effects on effectiveness estimates.
A novel statistical method using double negative controls can help account for hidden biases like healthcare seeking behavior in test-negative design studies of vaccine effectiveness.
Li et al. (2023) studied Infectious diseases (COVID-19). Double negative control inference method was evaluated on Vaccine effectiveness. A novel double negative control inference approach was developed to account for hidden biases in test-negative design studies and applied to estimate COVID-19 vaccine effectiveness.