Context: Gonorrhea, a highly communicable, sexually transmitted infection, remains a major public-health concern globally. In recent years, Zhejiang province, an eastern province, has had the highest incidence of gonorrhea in China.
Objective: The study intended to identify the geographic distribution patterns and spaciotemporal clustering characteristics of the disease's incidence in Zhejiang between 2016 and 2020, to understand the spatial epidemiology of gonorrhea and to pinpoint the locations with relatively high risks of gonorrhea, the hotspots, which could be the key areas for disease prevention and control.
Design: The research team performed a retrospective, spaciotemporal-clustering analysis of data about newly reported gonorrhea cases from January 2016 to December 2020 in Zhejiang province, using the China Information System for Disease Control and Prevention.
Setting: The study took place at the Zhejiang Provincial Institute of Dermatology in Huzhou, China.
Outcome measures: The research team: (1) used the Geographic Information System software-ArcGIS 10.8 software to draw statistical maps; (2) conducted a spatial-pattern clustering analysis at the district or county level; (3) performed an autocorrelation analysis using Getis-Ord (Gi*) statistics to detect spatial patterns and the hotspots of gonorrhea incidence; and (4) used SaTScan9.7 to analyze the space-time clusters.
Results: Zhejiang province reported 85 904 gonorrhea cases from 2016 to 2020, with a male to female ratio of 3.81:1. The average annual incidence rate of gonorrhea was 30.50 per 100 000 individuals in the population, ranging from 22.73 cases to 39.65 cases, and the annual incidence showed a significant downward trend over the five years (χ2 = 16.142, P < .001). The northern and central areas had a higher incidence than the southern area did. Autocorrelation analysis showed that the gonorrhea incidence had a significantly clustered distribution (Moran's I from 0.197 to 0.295, Z score from 4.749 to 6.909, P < .001). The high-high cluster areas were mainly in the urban districts of Hangzhou and some counties and districts of Jiaxing. The Gi* statistics further indicated that the hotspots of gonorrhea were mainly in Hangzhou, Jiaxing, and Huzhou. The Kuldorff's scan identified two clusters, mainly composed of 36 counties or districts in northern Zhejiang, such as Hangzhou and Jiaxing, and central Zhejiang, such as Jinhua and Shaoxing.
Conclusions: The gonorrhea incidence rates in northern and central Zhejiang from 2016 to 2020 were higher than those in southern Zhejiang. An area of relatively higher risk for gonorrhea existed mainly in the urban districts of Hangzhou and some counties and districts of Jiaxing, Jinhua, and Shaoxing. In the future, the research team plans to focus on strengthening the prevention and control measures against gonorrhea in those areas.