ArticleAmerican journal of epidemiology2019
Evaluating the Effectiveness of Vaccines Using a Regression Discontinuity Design.
Article in American journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- The Impact and Effectiveness of a Two-Dose Varicella Immunization Program Among School Children: Evidence from Quasi-experimental Analyses.Infectious diseases and therapy · 2026Article
- Designs for Vaccine Studies.Annual review of statistics and its application · 2025Article
- Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation.American journal of epidemiology · 2024Article
- Real-world effectiveness of the heterologous SOBERANA-02 and SOBERANA-Plus vaccine scheme in 2-11 years-old children during the SARS-CoV-2 Omicron wave in Cuba: a longitudinal case-population study.Lancet regional health. Americas · 2024Article
- Impact of intensive adherence counseling on viral load suppression and mortality among people living with HIV in Kampala, Uganda: A regression discontinuity design.PLOS global public health · 2023Article
- Measuring vaccine effectiveness from limited public health datasets: Framework and estimates from India's second COVID wave.Science advances · 2022Article
- Evaluation of post-introduction COVID-19 vaccine effectiveness: Summary of interim guidance of the World Health Organization.Vaccine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The regression discontinuity design (RDD), first proposed in the educational psychology literature and popularized in econometrics in the 1960s, has only recently been applied to epidemiologic research. A critical aim of infectious disease epidemiologists and global health researchers is to evaluate disease prevention and control strategies, including the impact of vaccines and vaccination programs. RDDs have very rarely been used in this context. This quasi-experimental approach using observational data is designed to quantify the effect of an intervention when eligibility for the intervention is based on a defined cutoff such as age or grade in school, making it ideally suited to estimating vaccine effects given that many vaccination programs and mass-vaccination campaigns define eligibility in this way. Here, we describe key features of RDDs in general, then specific scenarios, with examples, to illustrate that RDDs are an important tool for advancing our understanding of vaccine effects. We argue that epidemiologic researchers should consider RDDs when evaluating interventions designed to prevent and control diseases. This approach can address a wide range of research questions, especially those for which randomized clinical trials would present major challenges or be infeasible. Finally, we propose specific ways in which RDDs could advance future vaccine research.
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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.