关键词: 淋病, 发病率, 趋势, 时空聚类分析, 时空分析

Abstract: 【Abstract】 Objective To investigate the recent epidemic trends and spatiotemporal distribution characteristics of gonorrhea in China, and to provide a reference for precise prevention and control of gonorrhea. Methods Data on reported cases of gonorrhea in China （not including Hongkong, Macau and Taiwan regions of China） were collected from the Infectious Diseases Surveillance System of Chinese Disease Prevention and Control Information System from 2018 to 2023. The trends in reported incidence rates of gonorrhea in China were analyzed using the Joinpoint regression model. Global spatial autocorrelation analysis with the Moran′s index and global G-statistic, as well as local spatial autocorrelation analysis, were employed to explore the clustering patterns and hotspot regions of gonorrhea at the county level. In the spatiotemporal scanning analysis, a Poisson distribution model was employed to identify clusters of gonorrhea cases. Results The reported incidence rates of gonorrhea in China decreased from 9.59 per 100 000 in 2018 to 7.35 per 100 000 in 2023, with an average annual percent change of -4.9%, but this decreasing trend was not statistically significant （P = 0.11）. The reported incidence rates of gonorrhea at the county level in China exhibited a significant positive global spatial autocorrelation, with the global Moran′s indices ranging from 0.39 to 0.60 （all P < 0.001）; the Getis-Ord general G test statistic Z（G） values were all greater than 1.96, indicating a high-value clustering pattern of gonorrhea cases. The local spatial autocorrelation analysis showed that hotspot regions were predominantly distributed in southeastern coastal areas and southwestern China. A total of 70 clusters were identified through the spatiotemporal scanning analysis, and mainly located in southeastern coastal areas and southwestern China. Conclusions In recent 6 years, the overall reported incidence rates of gonorrhea in China showed a fluctuating decline; there was a significant spatiotemporal clustering characteristic with regard to gonorrhea epidemic at the county level in China, and the hotspot regions were basically consistent with the spatiotemporal clusters, which were mainly distributed in southeastern coastal areas and southwestern China. Further investigation into the causes and precise prevention and control measures are needed.

Key words: Gonorrhea, Incidence, Trend, Space-time clustering, Spatiotemporal analysis