Evidence map›Paper›PMID 38556390›Full record

ReviewVaccine2024

Review of mathematical models of Neisseria gonorrhoeae vaccine impact: Implications for vaccine development.

Thilini N Padeniya, Ben B Hui, James G Wood, David G Regan, Kate L Seib

Open access · hybridAbstract readReview
In one paragraph

Review in Vaccine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Thilini N PadeniyaInstitute for Glycomics, Griffith University, Gold Coast, Queensland, Australia. Electronic address: t.padeniya@griffith.edu.au.
Ben B HuiThe Kirby Institute, UNSW Sydney, New South Wales, Australia.
James G WoodSchool of Population Health, UNSW Sydney, New South Wales, Australia.
David G ReganThe Kirby Institute, UNSW Sydney, New South Wales, Australia.
Kate L SeibInstitute for Glycomics, Griffith University, Gold Coast, Queensland, Australia.
UNSW Sydney · AUGriffith University · AU

Funding

Using gonococcal TonB-dependent transporters as vaccine antigensU19AI144182 · NIAID · GEORGIA STATE UNIVERSITY · PI SEIB, KATE LOUISE · 2019 to 2023
$9.3M
Medical Research Council 1182443Medical Research Council 2017383NIAID NIH HHS U19 AI144182
6 · The paper itself

Abstract

An effective prophylactic vaccine for prevention of Neisseria gonorrhoeae infection would have a major impact on sexual and reproductive health worldwide. Interest in developing gonorrhoea vaccines is growing due to the reported high rates of N. gonorrhoeae infections globally, and the threat of antimicrobial resistance. Several gonorrhoea vaccine candidates are currently under evaluation and various mathematical models have been used to assess the potential population-level impact a gonorrhoea vaccine may have once available. Here we review key aspects of gonorrhoea vaccine mathematical modelling studies, including model structures, populations considered, and assumptions used as well as vaccine characteristics and implementation scenarios investigated. The predicted vaccine impact varied between studies, ranging from as little as ∼17 % reduction in N. gonorrhoeae prevalence after 30 years up to 100 % reduction after 5 years. However, all studies predicted that even a partially effective gonorrhoea vaccine could have a substantial impact in reducing N. gonorrhoeae prevalence or incidence, particularly when high coverage is achieved within either important risk groups or the overall sexually active population. As expected, higher vaccine efficacy against acquisition of N. gonorrhoeae and longer duration of protection were linked to greater reductions in infections. A vaccine that alters onward transmission could also substantially reduce infections. Several gaps and research needs have been identified by researchers in the field and via this narrative literature review. For example, future modelling to inform gonorrhoea vaccine development and implementation should consider additional populations that are at high risk of N. gonorrhoeae infection, especially in low- and middle-income settings, as well as the impact of vaccination on the potential adverse sexual and reproductive health outcomes of infection. In addition, more detailed and robust epidemiological, biological, and behavioural data is needed to enable more accurate and robust modelling of gonorrhoea vaccine impact to inform future scientific and public health decision-making.

Indexed as

Bacterial VaccinesGonorrheaModels, TheoreticalNeisseria gonorrhoeaeHumansPrevalenceVaccine DevelopmentVaccine EfficacyBacterial VaccinesGonorrheaGonorrhoeaMathematical modelNeisseria gonorrhoeaeVaccination

Identifiers

PMID38556390
PMCPMC12256113
OpenAlexW4393346423

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.