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. 2024 Dec 2;42(26):126493.
doi: 10.1016/j.vaccine.2024.126493. Epub 2024 Oct 30.

Evaluation of test-negative design estimates of influenza vaccine effectiveness in the context of multiple, co-circulating, vaccine preventable respiratory viruses

Aleda M Leis  1 , Abram Wagner  2 , Brendan Flannery  3 , Jessie R Chung  3 , Arnold S Monto  2 , Emily T Martin  2
Affiliations

Evaluation of test-negative design estimates of influenza vaccine effectiveness in the context of multiple, co-circulating, vaccine preventable respiratory viruses

Aleda M Leis et al. Vaccine. .

Abstract

Test-negative design (TND) studies are cornerstones of vaccine effectiveness (VE) monitoring for influenza. The introduction of SARS-CoV-2 and RSV vaccines complicate the analysis of this design, with control selection restriction based on other pathogen diagnosis proposed as a solution. We conducted a simulation study and secondary analysis of 2017-18 and 2018-19 TND estimates from a Southeast Michigan ambulatory population to evaluate RSV-status-based control restriction. Simulations suggest that with vaccine-preventable RSV, influenza VE could be moderately biased with RSV prevalence ≥25 % of controls. Real-world analysis showed 151 influenza-negative adults (10.4 %) had RSV detected from the enrollment nasal swab. There were minimal differences in results of adjusted models with or without RSV exclusion from control groups. Findings suggest that inclusion of RSV cases in the control group of TND studies for influenza VE, particularly where RSV is not vaccine preventable, does not currently pose a major concern for bias in VE estimates.

Keywords: Bias; Test-negative design; Vaccine efficacy.

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Conflict of interest statement

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Emily Toth Martin reports financial support was provided by Centers for Disease Control and Prevention. Aleda Leis reports financial support was provided by National Institutes of Health. Emily Toth Martin reports a relationship with Merck that includes: funding grants. Emily Toth Martin reports a relationship with Centers for Disease Control and Prevention that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1.
Fig. 1.
Illustration showing the results of simulation modeling when the correlation between influenza vaccination and RSV vaccination was a) low (RR = 2), b) moderate (RR = 5), and c) strong (RR = 8). The simulation model included fixed parameters influenza and RSV vaccination coverage of 60 %, RSV VE of 70 %, and incidence of medically attended influenza or RSV of 5 %. Influenza VE was tested at 30 %, 40 %, and 50 %.
Fig. 2.
Fig. 2.
Proportions of participants included in the real-world analysis of data who tested positive for influenza, tested positive for respiratory syncytial virus (RSV), or who were controls who tested negative for both influenza and RSV for a) the 2017/2018 influenza season and b) the 2018/2019 influenza season.
See this image and copyright information in PMC

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