Evidence map›Paper›PMID 39965640›Full record

ArticleJournal of the Royal Society, Interface2025

Vaccine failure mode determines population-level impact of vaccination campaigns during epidemics.

Da In Lee, Anjalika Nande, Thayer L Anderson, Michael Z Levy, Alison L Hill

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Da In Lee *Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Anjalika Nande *Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-1726-6633
Thayer L AndersonInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Michael Z LevyDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-4661-3764
Alison L HillInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-6583-3623

Funding

An immune system for the city: a new paradigm for control of urban disease vectorsR01AI146129 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI LEVY, MICHAEL Z, PAZ-SOLDAN, VALERIE ANDREA · 2019 to 2023
$3.3M
Quantification and prediction of treatment efficacy for HIV cure strategiesDP5OD019851 · OD · JOHNS HOPKINS UNIVERSITY · PI HILL, ALISON LYNN · 2014 to 2018
$2.1M
CDC HHSCDC HHS 6NU38FT000012NIAID NIH HHS R01 AI146129NIH HHS DP5 OD019851NIH HHS DP5OD019851NIH HHS R01AI146129
6 · The paper itself

Abstract

Vaccines are a crucial tool for controlling infectious diseases, yet rarely offer perfect protection. 'Vaccine efficacy' describes a population-level effect measured in clinical trials, but mathematical models used to evaluate the impact of vaccination campaigns require specifying how vaccines fail at the individual level, which is often impossible to measure. Does 90% efficacy imply perfect protection in 90% of people and no protection in 10% ('all-or-nothing') or that the per-exposure risk is reduced by 90% in all vaccinated individuals ('leaky') or somewhere in between? Here, we systematically investigate the role of vaccine failure mode in controlling ongoing epidemics. We find that the difference in population-level impact between all-or-nothing and leaky vaccines can be substantial when

Indexed as

COVID-19COVID-19 VaccinesEpidemicsImmunization ProgramsModels, BiologicalSARS-CoV-2VaccinationVaccine EfficacyHumansPandemicsCOVID-19 VaccinesCOVID-19epidemiologyinfectious diseasemathematical modellingvaccine efficacy

Identifiers

PMID39965640
PMCPMC11835492

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.