Global spatial clustering of mpox outbreaks: a geospatial analysis from 2022 to 2024
| dc.contributor.author | Pamukcu, Esra | |
| dc.contributor.author | Bayir, Tuba | |
| dc.contributor.author | Uysal, Serhat | |
| dc.date.accessioned | 2026-08-12T17:11:16Z | |
| dc.date.issued | 2025 | |
| dc.department | Fırat Üniversitesi | |
| dc.description.abstract | ObjectivesThis study aims to analyze the spatial distribution and clustering patterns of mpox cases worldwide from January 2022 to September 2024 using geospatial methods to identify high-risk areas.MethodsA retrospective spatial epidemiological analysis was conducted using WHO-confirmed mpox case data. Geographic Information Systems (GIS) were utilized for spatial visualization, while Moran's I and Local Indicators of Spatial Association (LISA) were applied to examine global and local spatial autocorrelation.ResultsGlobal Moran's I revealed significant positive spatial autocorrelation in 2022 (IM=0.144; p=0.006) and 2024 (IM=0.044; p=0.015), highlighting regional clustering of mpox transmission, while 2023 showed negative autocorrelation around China, (IM=-0.056;p=0.031), suggesting spatial outliers. LISA analysis identified High-High clusters in the Americas and Europe in 2022, in North America and several Asian regions in 2023, and in North America in 2024. The USA, China and the Democratic Republic of Congo emerged as high-burden countries.ConclusionsThe results demonstrate that spatial epidemiological approaches are an important tool for understanding the global spread of mpox and planning rapid interventions in high-risk regions. | |
| dc.identifier.doi | 10.1080/09603123.2025.2563794 | |
| dc.identifier.issn | 0960-3123 | |
| dc.identifier.issn | 1369-1619 | |
| dc.identifier.pmid | 40986646 | |
| dc.identifier.scopus | 2-s2.0-105017031477 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://doi.org/10.1080/09603123.2025.2563794 | |
| dc.identifier.uri | https://hdl.handle.net/11508/51076 | |
| dc.identifier.wos | WOS:001577099800001 | |
| dc.identifier.wosquality | Q3 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | PubMed | |
| dc.language.iso | en | |
| dc.publisher | Taylor & Francis Ltd | |
| dc.relation.ispartof | International Journal of Environmental Health Research | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_WoS_20260511 | |
| dc.subject | Monkeypox | |
| dc.subject | Spatial analysis | |
| dc.subject | Moran's I | |
| dc.subject | Public health | |
| dc.title | Global spatial clustering of mpox outbreaks: a geospatial analysis from 2022 to 2024 | |
| dc.type | Article |







