Effects of Confounding Bias in Coronavirus Disease 2019 (COVID-19) and Influenza Vaccine Effectiveness Test-Negative Designs Due to Correlated Influenza and COVID-19 Vaccination Behaviors

Correlated influenza and coronavirus disease 2019 (COVID-19) vaccination behaviors can bias influenza and COVID-19 vaccine effectiveness (VE) estimates from test-negative studies. Bias depends upon the proportion of controls with the other vaccine-preventable disease, correlation between vaccines, and true VE of both vaccines. Background The test-negative design is commonly used to estimate influenza and coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE). In these studies, correlated COVID-19 and influenza vaccine behaviors may introduce a confounding bias where controls are included with the other vaccine-preventable acute respiratory illness (ARI). We quantified the impact of this bias on VE estimates in studies where this bias is not addressed. Methods We simulated study populations under varying vaccination probabilities, COVID-19 VE, influenza VE, and proportions of controls included with the other vaccine-preventable ARI. Mean bias was calculated as the difference between estimated and true VE. Absolute mean bias in VE estimates was classified as low (<10%), moderate (10% to <20%), and high (>= 20%). Results Where vaccination probabilities are positively correlated, COVID-19 and influenza VE test-negative studies with influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ARI controls, respectively, underestimate VE. For COVID-19 VE studies, mean bias was low for all scenarios where influenza represented <= 25% of controls. For influenza VE studies, mean bias was low for all scenarios where SARS-CoV-2 represented <= 10% of controls. Although bias was driven by the conditional probability of vaccination, low VE of the vaccine of interest and high VE of the confounding vaccine increase its magnitude. Conclusions Where a low percentage of controls is included with the other vaccine-preventable ARI, bias in COVID-19 and influenza VE estimates is low. However, influenza VE estimates are likely more susceptible to bias. Researchers should consider potential bias and its implications in their respective study settings to make informed methodological decisions in test-negative VE studies.

Automated summary

Vaccine effectiveness estimates for influenza and COVID-19 may be biased due to correlated vaccination behaviors, and it is important to address this bias in test-negative studies.