TNDDR: Efficient and doubly robust estimation of COVID-19 vaccine effectiveness under the test-negative design

• URL: http://arxiv.org/abs/2310.04578v1
• Date: Fri, 6 Oct 2023 20:40:59 GMT
• Title: TNDDR: Efficient and doubly robust estimation of COVID-19 vaccine effectiveness under the test-negative design
• Authors: Cong Jiang, Denis Talbot, Sara Carazo, Mireille E Schnitzer
• Abstract summary: The test-negative design (TND) is susceptible to selection bias due to outcome-dependent sampling. We propose a one-step doubly robust and locally efficient estimator called TNDDR (TND doubly robust) We apply it to estimate COVID-19 VE in an administrative dataset of community-dwelling older people (aged $geq 60$y) in the province of Qu'ebec, Canada.
• Score: 0.46426477564038643
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While the test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-19 vaccine surveillance, it is susceptible to selection bias due to outcome-dependent sampling. Some studies have addressed the identifiability and estimation of causal parameters under the TND, but efficiency bounds for nonparametric estimators of the target parameter under the unconfoundedness assumption have not yet been investigated. We propose a one-step doubly robust and locally efficient estimator called TNDDR (TND doubly robust), which utilizes sample splitting and can incorporate machine learning techniques to estimate the nuisance functions. We derive the efficient influence function (EIF) for the marginal expectation of the outcome under a vaccination intervention, explore the von Mises expansion, and establish the conditions for $\sqrt{n}-$consistency, asymptotic normality and double robustness of TNDDR. The proposed TNDDR is supported by both theoretical and empirical justifications, and we apply it to estimate COVID-19 VE in an administrative dataset of community-dwelling older people (aged $\geq 60$y) in the province of Qu\'ebec, Canada.

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