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ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1427319
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Background: Making leprosy history in low-burden countries is a crucial step in achieving the World Health Organization's 2021-2030 Global Leprosy Strategy. Since leprosy has been contained at the national level in these countries, current efforts to eliminate leprosy have focused on specific leprosy high-risk areas. Quantifying the factors associated with leprosy risk would assist in identifying high-risk areas and the required efforts for leprosy elimination, which are still inadequate in these countries. To further progress a leprosy-free world, we investigated the associations between socioeconomic factors and the risk of leprosy in Yunnan Province, China. Methods: Socioeconomic factors and leprosy cases for 129 counties in Yunnan Province from 2004 to 2019 were collected. A spatiotemporal Bayesian model was used to evaluate the socioeconomic factors associated with leprosy risk. Results: 4361 leprosy cases were reported from 2004 to 2019 in Yunnan. Negative associations between disposable income per capita of rural residents (RR=0.947, 95%CI: 0.907, 0.989), population density (RR=0.920, 95%CI: 0.894, 0.945), the number of students enrolled by regular secondary schools (RR=0.990, 95%CI: 0.986, 0.994), and leprosy risk were found in Yunnan Province. The associations between the per capita product of the primary industry, proportion of male population, number of beds in health and medical institutions per 1000 population, and leprosy risk were not significant. Conclusions: This study revealed the associations between socioeconomic factors and leprosy risk in a low-burden country. These findings suggest that subsequent leprosy elimination efforts in Yunnan Province should prioritize rural areas, particularly those with lower population density and lower economic levels among farmers. Additionally, it is crucial to actively target poor rural farmers as a high-risk group for leprosy through strengthened early detection, multidrug therapy, and health education.
Keywords: Leprosy, Spatiotemporal study, Socioeconomic Factors, Disease mapping, Bayesian hierarchical spatiotemporal model
Received: 03 May 2024; Accepted: 11 Apr 2025.
Copyright: © 2025 Qian, 马, Wei, Peng, Li, Zhang, Yin and Shui. 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:
Fei Yin, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan Province, China
Tiejun Shui, Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
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.
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