Department of Social Medicine, School of Public Health, China Medical University, Shenyang, Liaoning, China (mainland).
Department of Health Statistics, School of Public Health, China Medical University, Shenyang, Liaoning, China (mainland).
Med Sci Monit. 2019 Jul 30;25:5657-5665. doi: 10.12659/MSM.915732.
BACKGROUND This study aimed to investigate trends in the epidemiology of the leading sexually transmitted diseases (STDs), acquired immune deficiency syndrome (AIDS), gonorrhea, and syphilis, in the 31 provinces of mainland China. MATERIAL AND METHODS This retrospective study analyzed the incidence data of STDs from official reports in China between 2004 and 2016. The grey model first order one variable, or GM (1,1), time series forecasting model for epidemiological studies predicted the incidence of STDs based on the annual incidence reports from 31 Chinese mainland provinces. Hierarchical cluster analysis was used to group the prevalence of STDs within each province. RESULTS The prediction accuracy of the GM (1,1) model was high, based on data during the 13 years between 2004 and 2016. The model predicted that the incidence rates of AIDS and syphilis would continue to increase over the next two years. Cluster analysis showed that 31 provinces could be classified into four clusters according to similarities in the incidence of STDs. Group A (Sinkiang Province) had the highest reported prevalence of syphilis. Group B included provinces with a higher incidence of gonorrhea, mainly in the southeast coast of China. Group C consisted of southwest provinces with a higher incidence of AIDS. CONCLUSIONS The GM (1,1) model was predictive for the incidence of STDs in 31 provinces in China. The predicted incidence rates of AIDS and syphilis showed an upward trend. Regional distribution of the major STDs highlights the need for targeted prevention and control programs.
本研究旨在调查中国大陆 31 个省份主要性传播疾病(性病)、艾滋病、淋病和梅毒的流行病学趋势。
本回顾性研究分析了 2004 年至 2016 年中国官方报告的性病发病率数据。灰色模型一阶单变量(GM(1,1))时间序列预测模型根据中国大陆 31 个省份的年度发病率报告预测了性病的发病率。层次聚类分析用于对每个省份的性病流行情况进行分组。
基于 2004 年至 2016 年 13 年的数据,GM(1,1)模型的预测精度较高。该模型预测艾滋病和梅毒的发病率将在未来两年继续上升。聚类分析显示,根据性病发病率的相似性,31 个省份可分为 4 组。A 组(新疆)梅毒报告发病率最高。B 组包括淋病发病率较高的省份,主要位于中国东南沿海。C 组由艾滋病发病率较高的西南省份组成。
GM(1,1)模型对中国 31 个省份的性病发病率具有预测性。预测的艾滋病和梅毒发病率呈上升趋势。主要性病的区域分布突出了需要有针对性的预防和控制计划。