了解2004-2021年我国淋病流行趋势,预测淋病患病率,为淋病的监测和管理提供基础理论和数据支持。通过中国公共卫生科学数据中心和国家疾病预防控制局收集2004-2021年中国淋病发病率数据,并对其发病率和流行病学特征进行分析。使用Joinpoint和自回归积分移动平均(ARIMA)模型进行统计分析。使用线性相关模型分析国内生产总值(GDP)与发病率之间的相关性。2004年至2021年,中国共报告淋病2,289,435例,报告的平均发病率为9.46/10万人,下降后呈上升趋势。淋病患者主要是20-30岁,2004年至2018年,1,034,847例(53.38%)。10~20岁年龄组发病率升高趋势最为明显(2004年5811例,2018年12752例,AAPC=6.1,P<.001)。2004-2021年我国淋病发病率与GDP呈负相关(r=-0.547,P=0.019)。2012-2018年各地区平均发病率增长率与地区GDP平均增长率的相关系数为0.673(P<0.01)。ARIMA模型的均方根误差(RMSE)为4.89%,表现出强大的性能。根据模型预测,2023年将有97,910例淋病病例。
To understand the epidemiological trend of gonorrhea in
China from 2004 to 2021, predict the prevalence of the disease, and provide basic theory and data support for monitoring and managing gonorrhea. Gonorrhea incidence data in
China from 2004 to 2021 were collected through the
China Public Health Science Data Center and National Administration of Disease Prevention and Control, and the incidence and epidemiological characteristics were analyzed. Statistical analysis was performed using Joinpoint and autoregressive integrated moving average (ARIMA) models. A linear correlation model was used to analyze the correlation between gross domestic product (
GDP) and the incidence rate. From 2004 to 2021, a total of 2,289,435 cases of gonorrhea were reported in China, with an average reported incidence rate of 9.46/100,000 people and a downward followed by an upward trend. Individuals with gonorrhea were primarily 20-30 y of age, with 1,034,847 cases (53.38%) from 2004 to 2018. The trend of increasing incidence was most obvious in the 10-20 age group (5,811 cases in 2004 to 12,752 cases in 2018, AAPC = 6.1, P < .001). The incidence of gonorrhea in
China was negatively correlated with
GDP from 2004 to 2021 (r = -0.547, P = .019). The correlation coefficient between the average incidence growth rate of each region from 2012 to 2018 and the average growth rate of regional
GDP was 0.673 (P < .01). The root mean square error (RMSE) of the ARIMA model was 4.89%, showing powerful performance. There would be 97,910 gonorrhea cases in 2023 as predicted by the model.