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Improving Assessment of Vaccine Effectiveness by Coupling Test-Negative Design Studies with Survival Models
Shangchen Song1, Matt Hitchings1,2, Yang Yang3
1Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
Medrxiv : the Preprint Server for Health Sciences
|December 18, 2025
Summary
The test-negative design (TND) can be a cohort study, allowing new analysis methods. A novel frailty model improves vaccine effectiveness evaluation, especially for COVID-19 vaccines against Omicron reinfection.
Area of Science:
- Epidemiology
- Biostatistics
- Vaccinology
Background:
- The test-negative design (TND) is a common observational study for vaccine effectiveness (VE) during COVID-19.
- TND is traditionally analyzed as a case-control study using logistic regression.
Purpose of the Study:
- Reframe TND as a cohort study to enable advanced analytical methods.
- Introduce and validate the Prentice, Williams, and Peterson gap-time (PWP-GT) frailty model for TND data.
- Estimate Pfizer COVID-19 vaccine effectiveness against infection and reinfection during Omicron variant circulation.
Main Methods:
- Framing TND as a cohort study.
- Applying the novel PWP-GT frailty model to TND data.
- Conducting simulation studies to compare model performance.
- Analyzing real-world data from the National COVID Cohort Collaborative (N3C).
Main Results:
- The PWP-GT frailty model accounts for recurrent infections and time-varying vaccination status.
- Simulation studies show the PWP-GT model outperforms conventional TND analysis methods.
- Real-world analysis estimated Pfizer vaccine effectiveness against infection and reinfection.
Conclusions:
- TND can be analyzed as a cohort study, expanding analytical possibilities.
- The PWP-GT frailty model offers a superior approach for TND analysis.
- The study provides crucial insights into COVID-19 vaccine effectiveness during Omicron variant circulation.
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