Abstract
BackgroundInfectious 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, whcih have implications for the reliability of effectiveness estimates using this design.MethodsWe 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.ResultsUsing 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.ConclusionsHybrid 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.
Highlights
Infectious disease outbreaks present unique challenges to study designs for vaccine evaluation
During Ebola virus disease (EVD) outbreaks, suspect cases may be tested because of: (i) presence of symptoms; or (ii) high-risk contact with a known case.[37,38]. We represent these testing reasons as distinct recruiting routes: self-reporting people who seek care for EVD-like symptoms; and people identified via active contact-tracing from a confirmed case
We demonstrate that public health response efforts can generate bias in the effectiveness estimates of a conventional test-negative design (TND) study
Summary
Study designs to evaluate new vaccines during outbreaks and pandemics are challenging for logistical, epidemiological, social and ethical reasons.[1,2,3,4,5,6,7] Novel and poorly understood pathogens can rapidly overwhelm local health systems, subsequently enabling other crises, or can require intensive control policies, complicating both response efforts and research.[8,9,10,11] some key pathogens are only routinely observable under these conditions, like Ebola virus disease (EVD) and others on the World Health Organization (WHO) R&D Blueprint priority list.[12]. During outbreaks of highly pathogenic infections there may be pressure to introduce experimental vaccines as quickly as possible,[13,14] as well as resistance to classical randomized controlled trials.[15] For EVD, the existence of a licensed vaccine (rVSV-ZEBOV)[16,17,18,19] further complicates trials for new vaccines Such circumstances suggest alternative evaluation strategies, and a test-negative design (TND) study has been proposed to evaluate a two-dose vaccine in eastern Democratic Republic of Congo (DRC).[20,21,22] This design estimates vaccine effectiveness from the odds ratio for test outcome conditional on vaccination status, and has lower misclassification bias than traditional case-control studies.[23,24].
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