Methods for Estimating VE Using Routine School Testing Data with Differential Testing Behavior

Music City Center 

During the COVID-19 pandemic, many school systems implemented opt-in regular testing for students to track the spread of disease and detect cases early. Beyond the primary use of these testing programs as surveillance, the observational data collected from these programs can be leveraged to measure vaccine effectiveness (VE) among school-aged children. The data from these sources offers complicated challenges to the standard assumptions of vaccine effectiveness methodology, specifically when there is evidence of differential testing behavior between the vaccinated and unvaccinated groups. To combat this issue, we explore approaches to characterize the differences in testing behavior to improve the implementation of standard VE methodology. We apply 3 methods for measuring VE to the observational data: a target trial emulation approach with matching of participants across vaccination groups, a time-varying effect model of vaccination, and a test-negative design. For these methods we compare the losses to sample size due to study design, discuss approaches to adjust for differential testing behavior, and consider additional sources of bias due to unmet assumptions.

Vaccine Effectiveness

Target Trial Emulation

Test-negative Design

Time-varying Effect

COVID-19

Observational Study 

ENAR