Payne, Amanda B.Ciesla, Allison AvrichRowley, Elizabeth A. K.Weber, Zachary A.Reese, Sarah E.Ong, Toan C.Vazquez-Benitez, GabrielaNaleway, Allison L.Klein, Nicola P.Embi, Peter J.Grannis, Shaun J.Kharbanda, Anupam B.Gaglani, ManjushaTenforde, Mark W.Link-Gelles, RuthVISION Network2025-03-242025-03-242023Payne AB, Ciesla AA, Rowley EAK, et al. Impact of accounting for correlation between COVID-19 and influenza vaccination in a COVID-19 vaccine effectiveness evaluation using a test-negative design. Vaccine. 2023;41(51):7581-7586. doi:10.1016/j.vaccine.2023.11.025https://hdl.handle.net/1805/46503Test-negative-design COVID-19 vaccine effectiveness (VE) studies use symptomatic SARS-CoV-2-positive individuals as cases and symptomatic SARS-CoV-2-negative individuals as controls to evaluate COVID-19 VE. To evaluate the potential bias introduced by the correlation of COVID-19 and influenza vaccination behaviors, we assessed changes in estimates of VE of bivalent vaccines against COVID-19-associated hospitalizations and emergency department/urgent care (ED/UC) encounters when considering influenza vaccination status or including or excluding influenza-positive controls using data from the multi-state VISION vaccine effectiveness network. Analyses included encounters during October 2022 - February 2023, a period of SARS-CoV-2 and influenza cocirculation. When considering influenza vaccination status or including or excluding influenza-positive controls, COVID-19 VE estimates were robust, with most VE estimates against COVID-19-associated hospitalization and ED/UC encounters changing less than 5 percentage points. Higher proportions of influenza-positive patients among controls, influenza vaccination coverage, or VE could impact these findings; the potential bias should continue to be assessed.en-USPublisher PolicyCOVID-19InfluenzaNegativeSARS-CoV-2TestVaccine effectivenessArticle