Emulating a vaccine target trial under unmeasured confounding: single and double negative control methods

Estimating vaccine effectiveness (VE) for symptom-driven outcomes in observational settings remains challenging due to unmeasured differences in health-seeking behavior between vaccine groups. This challenge persists even with target trial emulation, which primarily addresses design-related biases. The test negative design, a popular alternative design for estimating VE, can reduce bias due to unmeasured confounding by health-seeking but often deviates from the design principles of trial emulation. Here, we emulate a target trial to estimate relative VE of COVID-19 bivalent booster in a cohort of Kaiser Permanente of Northern California members and provide evidence for residual unmeasured confounding through negative controls. We then propose two approaches for estimating VE that operate within the target trial framework but allow for unmeasured confounding. The first uses test-negative illness as a negative control outcome and corrects for bias under the assumption of equi-confounding on the multiplicative scale. The second relaxes equi-confounding but requires an additional (valid) negative control. The two approaches yield similar estimates of 1-year relative VE (11.1% vs. 15.9%) but are both qualitatively different from traditional methods (VE: − 14.5%). These approaches illustrate the flexibility of the target trial framework which can retain sound design principles while accommodating alternative identification strategies.