Evidence map›Paper›PMID 40067846›Full record

ArticlePloS one2025

Geographical distribution and the impact of socio-environmental indicators on incidence of Mpox in Ontario, Canada.

Chigozie Louisa J Ugwu, Ali Asgary, Jianhong Wu, Jude Dzevela Kong, Nicola Luigi Bragazzi, James Orbinski, Woldegebriel Assefa Woldegerima

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Chigozie Louisa J UgwuLaboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.ORCID 0000-0001-5013-2253
Ali AsgaryThe Advanced Disaster, Emergency and Rapid Response Program, York University, Toronto, Canada.
Jianhong WuLaboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.
Jude Dzevela KongAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Toronto, Canada.
Nicola Luigi BragazziLaboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.
James OrbinskiThe Dahdaleh Institute for Global Health Research, York University, Toronto, Canada.
Woldegebriel Assefa WoldegerimaLaboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.ORCID 0000-0002-0336-7831

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOntario, being one of Canada's largest provinces, has been central to the high incidence of human Mpox. Research is scarce on how socio-environmental factors influence Mpox incidences. This study seeks to explore potential geographical correlations and the relationship between indicators of social marginalization and Mpox incidence rate in Ontario. METHODOLOGY: We used surveillance data on confirmed human Mpox cases from May 1, 2022, to March 31, 2024, extracted from the Public Health Ontario website for this study. Spatial autocorrelation of Mpox incidence was investigated using spatial methods including Moran's Index, Getis-Ord Gi*statistic, and spatial Poisson scan statistic. Following this, we adopted a generalized Poisson regression (GPR) model to estimate the incidence rate ratios (IRRs) based on the association between Ontario PHU-level marginalization and Mpox incidence, while adjusting for age and sex. The goodness-of-fit of the models was assessed using the Log Likelihood (LL), Akaike Information Criterion (AIC), Akaike's Information Criterion corrected (AICc), and the Bayesian Information Criterion (BIC).

resultsOur analysis revealed significant localized spatial heterogeneity in Mpox incidence across Ontario. Statistically significant local clusters of Mpox cases were identified in Toronto ([Formula: see text] ), Ottawa ([Formula: see text]), and a secondary cluster, overlapping Hamilton PHU with nine local districts ([Formula: see text]), all with [Formula: see text]. The incidence rate of Mpox was statistically significantly associated with a higher proportion of ethnic concentration (racialized groups, migrants, or visible minorities) [Formula: see text], gender [Formula: see text] and higher residential instability [Formula: see text].

conclusionWe identified major Mpox hotspots in Toronto. According to our model results, the high incidence rate may be influenced by the greater population of internal migrants and younger individuals. Based on these insights, we recommend targeted interventions in the high-risk neighborhoods. Efforts to improve Mpox diagnosis and promote health equity among socioeconomically vulnerable populations, including racial and ethnic minorities, should be implemented.

Indexed as

Mpox, MonkeypoxSocioeconomic FactorsAdolescentAdultAgedChildChild, PreschoolFemaleHumansIncidenceMaleMiddle AgedOntarioYoung Adult

Identifiers

PMID40067846
PMCPMC11896077

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.