Use of self-reported vaccination status can bias vaccine effectiveness estimates from test-negative studies. (11th April 2019) - Jackson, Michael L.
Abstract: Introduction: A number of national/multi-national networks provide annual estimates of influenza vaccine effectiveness (VE) based on the test-negative design. Most of these networks use subject self-reports to define influenza vaccination history. In this study, we used simulations to estimate the degree to which self-reported vaccination status can bias test-negative VE estimates. Methods: We simulated a population whose members are at risk for acute respiratory illness (ARI) due to influenza and for ARI due to other respiratory pathogens. Vaccination was assumed to reduce the risk of influenza but not of non-influenza ARI. We simulated a range of possible values for VE and for vaccine coverage. Across simulations, we varied the sensitivity and specificity of self-reported vaccination status relative to true vaccination. We estimated bias as the percent difference in VE in the presence of misclassification relative to true simulated VE. Results: Assuming self-report has sensitivity of 95% and specificity of 90%, estimated VE underestimated true VE by 16% (95% confidence interval, 4–30%). Decreasing specificity of self-reports resulted in greater bias than decreasing sensitivity of self-reports. Bias also increased as vaccine coverage decreased. Conclusions: The use of self-reported influenza vaccination history can meaningfully bias influenza VE in test-negative studies. Researchers using test-negative designs should attempt to supplement or validate self-reported vaccination history using additional data sources.