ArticleBMC medical research methodology2025
Over- and under-estimation of vaccine effectiveness.
Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Effectiveness of a trivalent inactivated split-virion influenza vaccine (Tri Fluvac) in Thailand: a phase IV test-negative case-control study.The Lancet regional health. Southeast Asia · 2026Article
- Viral Respiratory Epidemic Modeling of Societal Segregation Based on Vaccination Status.Cureus · 2023Article
- MAM: Flexible Monte-Carlo Agent based model for modelling COVID-19 spread.Journal of biomedical informatics · 2023Article
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe effectiveness of SARS-CoV-2 vaccines against infection has been a subject of debate, with varying results reported in different studies, ranging from 60-95% vaccine effectiveness (VE). This range is striking when comparing two studies conducted in Israel at the same time, as one study reported VE of 90-95%, while the other study reported only ~ 80%. We argue that this variability is due to inadequate accounting for indirect protection provided by vaccines, which can block further transmission of the virus. MATERIALS AND
methodsWe developed a novel analytic heterogenous infection model and extended our agent-based model of disease spread to allow for heterogenous interactions between vaccinated and unvaccinated across close-contacts and regions. We applied these models on real-world regional data from Israel from early 2021 to estimate VE using two common study designs: population-based and secondary infections.
resultsOur results show that the estimated VE of a vaccine with efficacy of 85% can range from 70-95% depending on the interactions between vaccinated and unvaccinated individuals. Since different study designs capture different levels of interactions, we suggest that this interference explains the variability across studies. Finally, we propose a methodology for more accurate estimation without knowledge of interactions. DISCUSSIONS AND
conclusionsOur study highlights the importance of considering indirect protection when estimating vaccine effectiveness, explains how different study designs may report biased estimations, and propose a method to overcome this bias. We hope that our models will lead to more accurate understanding of the impact of vaccinations and inform public health policy. CLINICAL TRIAL NUMBER: Not applicable.
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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.