Evidence map›Paper›PMID 41340045›Full record

ArticleBMC infectious diseases2025

Pre-exposure vaccination in the high-risk population is crucial in controlling mpox resurgence in Canada.

Andrew Omame, Sarafa A Iyaniwura, Adeniyi Ebenezer, Qing Han, Xiaoying Wang, Nicola L Bragazzi, Jude D Kong, Woldegebriel Aseefa Woldegerima

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Andrew Omame *Disease-Informed Modelling, Methods, and Systems (DIMMS) Lab, Department of Mathematics and Statistics, York University, Toronto, ON, Canada.
Sarafa A Iyaniwura *Biostatistics, Bioinformatics, and Epidemiology Program, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA.
Adeniyi EbenezerAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Department of Mathematics and Statistics, York University, Toronto, ON, M3J 1P3, Canada.
Qing HanAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Department of Mathematics and Statistics, York University, Toronto, ON, M3J 1P3, Canada.
Xiaoying WangDepartment of Mathematics & Statistics, Trent University Peterborough, Peterborough, ON, Canada.
Nicola L BragazziDepartment of Clinical Pharmacy, Saarland University, 66123, Saarbrücken, Germany.
Jude D KongAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Department of Mathematics and Statistics, York University, Toronto, ON, M3J 1P3, Canada. jude.kong@utoronto.ca.
Woldegebriel Aseefa WoldegerimaDisease-Informed Modelling, Methods, and Systems (DIMMS) Lab, Department of Mathematics and Statistics, York University, Toronto, ON, Canada. wassefaw@yorku.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As mpox spread continues across several endemic and non-endemic countries around the world, vaccination has become an integral part of the global response to control the epidemic. Some vaccines have been recommended for use against mpox by the World Health Organization (WHO). As the roll-out of mpox vaccines continue across the globe, it is imperative to develop mathematical models to support public health officials and governments agencies in optimizing vaccination strategies to curtail the resurgence of mpox. In this article, we develop a compartmental mathematical model to investigate the impact of vaccination in controlling a potential mpox resurgence in Canada. The model categorizes individuals into high- and low-risk groups and incorporates pre-exposure vaccination in the high-risk group and post-exposure vaccination in the high- and low-risk groups. The vaccine-free version of the model was calibrated to the daily reported cases of mpox in Canada from April to October 2022, from which we estimated key model parameters, including the sexual and non-sexual transmission rates. Furthermore, we calibrated the full model to the daily reported cases of mpox in Canada in 2024, to estimate the current mpox vaccination rates in Canada. Our results highlight the importance of pre-exposure vaccination in the high-risk group on controlling a potential resurgence of mpox in Canada, and the minimal effects of post-exposure vaccination in the high- and low-risk groups on the outbreak. In addition, our model predicts the possibility of mpox becoming endemic in Canada, in the absence of pre-exposure vaccination in the high-risk group. Overall, our modeling result suggests that pre-exposure vaccination in the high-risk group is crucial in controlling mpox outbreak in Canada. Stepping up this vaccination is sufficient to avert a potential mpox resurgence in Canada.Clinical trial number Not applicable.

Indexed as

Mpox, MonkeypoxPre-Exposure ProphylaxisSmallpox VaccineVaccinationCanadaFemaleHumansMaleModels, TheoreticalSmallpox VaccineEpidemicsHigh-riskLow-riskMpoxPost-exposure vaccinationPre-exposure vaccinationVaccination

Identifiers

PMID41340045
PMCPMC12781497

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.