ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
This article is part of the Research TopicMathematical Modelling and Data Analysis in Infectious DiseasesView all 7 articles
Spatial Patterns and Socio-Environmental Determinants of Gonorrhea Incidence in China
Provisionally accepted
- 1Xiamen Haicang Hospital, Xiamen, China
- 2QianDongNanZhou Center for Disease Control and Prevention, QianDongNanZhou, China
- 3Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai Municipal Hospital of Traditional Chinese Medicine, China
- 4Xingtai Center for Disease Control and Prevention, Xingtai, China
- 5Nanjing Lishui Dongping Street Health Center, Nanjing, China
- 6Community Health Service Center of Jiuxian Tongliang District, Chongqing, China
- 7Fuwai Central China Cardiovascular Hospital, Zhengzhou, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Abstract Introduction Gonorrhea is a major sexually transmitted infection in China, showing distinct regional clustering and spatial heterogeneity. Understanding its geographical distribution and influencing factors is crucial for targeted prevention. Methods We analyzed 2022 gonorrhea incidence across 31 Chinese provinces using both traditional and spatial statistical approaches, including descriptive statistics, spatial autocorrelation, multiple linear regression (MLR), and spatial error models (SEM). Factors from five categories—economic, demographic, environmental, educational, and healthcare-related — were examined. The Geodetector method was additionally used to assess factor contributions and interactions. Results Three key findings emerged: (1) Significant regional disparities in gonorrhea incidence were observed, with high-high clusters detected in southern provinces and low-low clusters in northern regions.; (2) SEM outperformed MLR, confirming stronger effects of illiteracy rate, bed utilization rate, sex ratio, and PM2.5 concentration while demonstrating better model fit (higher R2, log-likelihood; lower AIC); (3) Sex ratio was identified as a core determinant, with interaction effects (particularly bed utilization rate and sex ratio) amplifying individual impacts. Conclusion These results support spatially tailored intervention strategies that integrate sociodemographic and environmental factors for effective gonorrhea prevention.
Keywords: Gonorrhea incidence, spatial autocorrelation, multiple linear regression, Spatial error model, Geodetector
Received: 04 Sep 2025; Accepted: 17 Nov 2025.
Copyright: © 2025 Hu, Yang, Cai, Li, Zhang, Xiao and Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mingyang Yu, 2296991140@qq.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.