Potential Test-Negative Design Study Bias in Outbreak Settings: Application to Ebola vaccination in Democratic Republic of Congo

Background Infectious disease outbreaks present unique challenges to study designs for vaccine evaluation. Test-negative design (TND) studies have previously been used to estimate vaccine effectiveness and have been proposed for Ebola virus disease (EVD) vaccines. However, there are key differences in how cases and controls are recruited during outbreaks and pandemics of novel pathogens that have implications for the reliability of effectiveness estimates using this design. Methods We use a modelling approach to quantify TND bias for a prophylactic vaccine under varying study and epidemiological scenarios. Our model accounts for heterogeneity in vaccine distribution and for two potential routes to testing and recruitment into the study: self-reporting and contact-tracing. We derive conventional and hybrid TND estimators for this model and suggest ways to translate public health response data into the parameters of the model. Results Using a conventional TND study, our model finds biases in vaccine effectiveness estimates. Bias arises due to differential recruitment from self-reporting and contact-tracing, and due to clustering of vaccination. We estimate the degree of bias when recruitment route is not available, and propose a study design to eliminate the bias if recruitment route is recorded. Conclusions Hybrid TND studies can resolve the design bias with conventional TND studies applied to outbreak and pandemic response testing data, if those efforts collect individuals’ routes to testing. Without route to testing, other epidemiological data will be required to estimate the magnitude of potential bias in a conventional TND study. Since these studies may need to be conducted retrospectively, public health responses should obtain these data, and generic protocols for outbreak and pandemic response studies should emphasize the need to record routes to testing. Key Messages - Conventional Test-Negative Design (TND) studies can be biased when follow-up of cases leads to testing and recruitment, which occurs for example during contact tracing. - A hybrid TND estimator can eliminate this bias, if individual testing routes are recorded. - The related bias in the conventional TND estimator can be quantified using epidemiological measures. - If testing route data is unavailable, bias can be limited by other study measures.