Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project.

ABSTRACT:

Background

Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the DRIVE multi-country network of sites conducting test-negative design (TND) studies.

Methods

We constructed a directed acyclic graph (DAG) to map the relationship between influenza vaccination, medically attended influenza infection, confounders, and other variables. Additionally, we used the Development of Robust and Innovative Vaccines Effectiveness (DRIVE) data from the 2018/2019 and 2019/2020 seasons to explore the effect of covariate adjustment on IVE estimates. The reference m

SUBMITTER: Stuurman AL 

PROVIDER: S-EPMC9835455 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature