Evidence map›Paper›PMID 40898057›Full record

ArticleBMC public health2025

How place shapes genital herpes simplex distribution in South Korea: a Bayesian spatial analysis using National Health Insurance Service data.

Joonsu Jang, Seyul Park, Byung Chul Chun

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

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Joonsu JangDepartment of Preventive Medicine, Korea University College of Medicine, Goryeodae-Ro 73, Seongbuk-Gu, Seoul, 02841, Republic of Korea.ORCID http://orcid.org/0009-0005-5763-4703
Seyul ParkDepartment of Preventive Medicine, Korea University College of Medicine, Goryeodae-Ro 73, Seongbuk-Gu, Seoul, 02841, Republic of Korea.
Byung Chul ChunDepartment of Preventive Medicine, Korea University College of Medicine, Goryeodae-Ro 73, Seongbuk-Gu, Seoul, 02841, Republic of Korea. chun@korea.ac.kr.ORCID http://orcid.org/0000-0001-6576-8916

Funding

Korea Disease Control and Prevention Agency 2021-07-010
6 · The paper itself

Abstract

backgroundGenital herpes simplex (GHS) infections have increased in South Korea over the past decade, yet the geographic distribution of GHS incidence rates remains poorly understood. This study examined the geographic distribution of GHS incidence rates across South Korea and identified place-specific risk factors to inform targeted prevention strategies.

methodsUsing the Korean National Health Insurance Service data from 2019, we analyzed age-standardized GHS incidence rates across 250 municipalities in South Korea. Spatial autocorrelation was assessed using Global Moran's I and hot spots were identified using the Getis-Ord Gi* analysis. Bayesian hierarchical regression models were used to quantify the associations between regional risk factors and GHS risk while accounting for spatial dependence. The area-specific posterior mean was used to map the relative risk (RR) of GHS.

resultsIn total, 182,289 patients with GHS were identified. Significant positive spatial autocorrelation was observed (Moran's I = 0.431, p < 0.001), with distinct hot spots concentrated in the Seoul Capital Area. After adjusting for covariates and spatial effects, the proportion of single-person households (RR = 1.026, 95% credible interval (CrI) = 1.017-1.035) and sexual violence risk (2nd quartile: RR = 1.106, 95% CrI = 1.018-1.201; 3rd quartile: RR = 1.095, 95% CrI = 1.003-1.195) were significant place-based risk factors associated with higher GHS incidence rates. High-risk areas for GHS were found in the Seoul Capital Area and some mid-southern cities.

conclusionsThis study reveals distinct geographic patterns in GHS incidence rates that are not fully explained by demographic composition alone. The significant associations with household structure and sexual violence risk suggest that place-specific social contexts influence GHS incidence rates. These findings highlight the importance of spatially targeted interventions to address contextual vulnerabilities in regions with high GHS incidence rates.

Indexed as

Herpes GenitalisAdolescentAdultBayes TheoremFemaleHumansIncidenceMaleMiddle AgedNational Health ProgramsRepublic of KoreaRisk FactorsSpatial AnalysisYoung AdultBayesian spatial modelingGenital herpes simplexSexually transmitted infectionsSouth KoreaSpatial epidemiology

Identifiers

PMID40898057
PMCPMC12403936

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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.