Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China.
BMC Public Health. 2024 Feb 14;24(1):465. doi: 10.1186/s12889-024-17859-6.
Despite many efforts to control leprosy worldwide, it is still a significant public health problem in low- and middle-income regions. It has been endemic in China for thousands of years, and southwest China has the highest leprosy burden in the country.
This observational study was conducted with all newly detected leprosy cases in southwest China from 2010 to 2020. Data were extracted from the Leprosy Management Information System (LEPMIS) database in China. The Joinpoint model was used to determine the time trends in the study area. Spatial autocorrelation statistics was performed to understand spatial distribution of leprosy cases. Spatial scan statistics was applied to identify significant clusters with high rate.
A total of 4801 newly detected leprosy cases were reported in southwest China over 11 years. The temporal trends declined stably. The new case detection rate (NCDR) dropped from 4.38/1,000,000 population in 2010 to 1.25/1,000,000 population in 2020, with an average decrease of 12.24% (95% CI: -14.0 to - 10.5; P < 0.001). Results of global spatial autocorrelation showed that leprosy cases presented clustering distribution in the study area. Most likely clusters were identified during the study period and were frequently located at Yunnan or the border areas between Yunnan and Guizhou Provinces. Secondary clusters were always located in the western counties, the border areas between Yunnan and Sichuan Provinces.
Geographic regions characterized by clusters with high rates were considered as leprosy high-risk areas. The findings of this study could be used to design leprosy control measures and provide indications to strengthen the surveillance of high-risk areas. These areas should be prioritized in the allocation of resources.
尽管全球范围内为控制麻风病付出了诸多努力,但它在中低收入地区仍是一个重大的公共卫生问题。麻风病在中国流行了数千年,中国西南地区的麻风病负担最重。
本观察性研究纳入了 2010 年至 2020 年中国西南地区新发现的所有麻风病病例。数据从中国麻风病管理信息系统(LEPMIS)数据库中提取。采用 Joinpoint 模型确定研究地区的时间趋势。进行空间自相关统计,以了解麻风病病例的空间分布。应用空间扫描统计识别高发病率的显著聚集区。
11 年间,中国西南地区共报告了 4801 例新发现的麻风病病例。时间趋势稳定下降。新病例检出率(NCDR)从 2010 年的 4.38/100 万下降到 2020 年的 1.25/100 万,平均下降 12.24%(95%CI:-14.0 至-10.5;P<0.001)。全球空间自相关结果表明,研究地区的麻风病病例呈聚集分布。在研究期间确定了最有可能的聚集区,这些聚集区通常位于云南省或云南省与贵州省交界处。二级聚集区则始终位于西部县、云南省与四川省交界处。
存在高发病率聚集区的地理区域被认为是麻风病高风险地区。本研究结果可用于设计麻风病控制措施,并为加强高风险地区的监测提供指示。这些地区应在资源分配中优先考虑。