ArticleJournal of the American Statistical Association2024
Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness.
Article in Journal of the American Statistical Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Validity of influenza vaccine effectiveness calculations using a test-negative design in Thailand.American journal of epidemiology · 2026Article
- COVID-19 vaccine effectiveness in patients with lung cancer: challenges in the Omicron era.BMC infectious diseases · 2026Article
- Unmeasured confounding and misclassification in studies estimating vaccine effectiveness against hospitalisation and death using electronic health records (EHRs): an evaluation of a multi-country European retrospective cohort study.BMC medical research methodology · 2025Article
- Immune Correlates and Vaccine Immunobridging: Statistical Innovations, Challenges, and Opportunities.The Journal of infectious diseases · 2025Review
- Estimating cardiovascular effects of influenza vaccination in older adults: a target trial emulation using proximal causal inference.EClinicalMedicine · 2025Article
- Improved Methods for Vaccine Effectiveness Studies.The Journal of infectious diseases · 2025Article
- Impact of unequal testing on vaccine effectiveness estimates across two study designs: a simulation study.Nature communications · 2025Article
- Evaluating the Test-Negative Design for COVID-19 Vaccine Effectiveness Using Randomized Trial Data: A Secondary Cross-Protocol Analysis of 5 Randomized Clinical Trials.JAMA network open · 2025Article
- Estimated Effectiveness of Nirsevimab Against Respiratory Syncytial Virus.JAMA network open · 2025Article
- A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness Under the Test-Negative Design: Analysis of Québec Administrative Data.Statistics in medicine · 2025Article
- Symptoms Six Weeks After COVID-19 Are Reduced Among US Health Care Personnel Receiving Additional Vaccine Doses During the Omicron Period, December 2021-April 2022.Open forum infectious diseases · 2024Article
- Regression-Based Proximal Causal Inference.American journal of epidemiology · 2024Article
- Review
- Design and analysis heterogeneity in observational studies of COVID-19 booster effectiveness: A review and case study.Science advances · 2023Review
- INTRODUCING PROXIMAL CAUSAL INFERENCE FOR EPIDEMIOLOGISTS.American journal of epidemiology · 2023Article
- Coronavirus Disease 19 (COVID-19) Vaccine Effectiveness Against Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection During Delta-Dominant and Omicron-Dominant Periods in Japan: A Multicenter Prospective Case-control Study (Factors Associated with SARS-CoV-2 Infection and the Effectiveness of COVID-19 Vaccines Study).Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Noninterventional studies in the COVID-19 era: methodological considerations for study design and analysis.Journal of clinical epidemiology · 2023Article
- The impact of repeated vaccination on relative influenza vaccine effectiveness among vaccinated adults in the United Kingdom.Epidemiology and infection · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world settings, such as Influenza, Rotavirus, Dengue fever, and more recently COVID-19. In a TND study, individuals who experience symptoms and seek care are recruited and tested for the infectious disease which defines cases and controls. Despite TND's potential to reduce unobserved differences, in healthcare seeking behavior (HSB) between vaccinated and unvaccinated subjects, it remains subject to various potential biases. First, residual confounding may remain due to unobserved HSB occupation as healthcare worker, or previous infection history. Second, because selection into the TND sample is a common consequence of infection and HSB, collider stratification bias may exist when conditioning the analysis on tested samples, which further induces confounding by latent HSB. In this paper, we present a novel approach to identify and estimate vaccine effectiveness in the target population by carefully leveraging a pair of negative control exposure and outcome variables to account for potential hidden bias in TND studies. We illustrate our proposed method with extensive simulations and an application to study COVID-19 vaccine effectiveness using data from the University of Michigan Health System.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.