2013-2022年北京市东城区肺结核报告发病流行特征及发病预测分析OA北大核心CSTPCD
Analysis of the epidemiological characteristics and prediction for the reported incidence of pulmonary tuberculosis in Dongcheng District,Beijing from 2013 to 2022
目的:分析2013-2022年北京市东城区肺结核报告发病流行特征和变化规律,运用季节性自回归滑动平均混合模型(seasonal autoregressive integrated moving average,SARIMA)对既往报告发病数建模并预测2023年1-6月报告发病情况,为本区肺结核防控措施提供参考数据.方法:通过"中国疾病预防控制信息系统"子系统"传染病监测系统"获取2013年1月至2023年6月北京市东城区肺结核报告发病数据,分析2013-2022年肺结核报告发病流行特征;使用2013-2022年月报告发病数建立SARIMA模型,并用2023年1-6月报告发病数据进行模型预测和验证.结果:2013-2022年北京市东城区累计报告2505例活动性肺结核患者,年平均报告发病率28.81/10万,报告发病率最高为2013年(38.68/10万,379例),最低为2020年(23.30/10万,185例),总体呈下降趋势(x2趋势=25.371,P<0.001),年均递降率为5.26%.病原学阳性肺结核检出率最高为2022年(57.74%,97/168),最低为2017年(30.71%,74/241),总体呈逐年上升趋势(x2趋势=29.945,P<0.001).男性肺结核年均报告发病率为36.85/10万(1559例),明显高于女性的21.20/10万(946例),男女性别比为1.73:1,差异有统计学意义(x2=184.738,P<0.001);20~29 岁组(19.88%,498/2505)和离退人员(37.72%,945/2505)患者构成比较高;患者主要集中在永定门外街道(11.38%,285/2505).季节分析显示,季节指数在0.83~1.09之间,呈周期性波动,流行期主要集中在3-8月和12月.SARIMA(0,1,2)(1,2,1)12模型较好的拟合报告发病趋势(AIC=657.67),预测发病数平均相对误差为-17.72%,预测精确度较高(均方根误差为5.188,平均绝对百分比误差为22.01%).结论:2013-2022年北京市东城区肺结核报告发病呈稳定下降趋势,以男性、离退人员为主,需注重春夏季节、老年和青壮年人群的结核病防控及宣教工作.SARIMA(0,1,2)(1,2,1)12模型能较好拟合本区肺结核报告发病变化趋势且预测效果良好.
Objective:To analyze the epidemic characteristics and changing rules of tuberculosis reported in Dongcheng District of Beijing from 2013 to 2022.The reported incidence from January to June 2023 was predicted through modeling the previously reported data using the seasonal autoregressive integrated moving average(SARIMA),so as to provide reference for tuberculosis prevention and control measures in the district.Methods:The reported incidence data of pulmonary tuberculosis in Dongcheng District,Beijing from January 2013 to June 2023 was obtained through the"Infectious Disease Monitoring System"subsystem of the"China Disease Prevention and Control Information System".The epidemic characteristics of reported pulmonary tuberculosis from 2013 to 2022 were analyzed.The SARIMA model was established using monthly reported incidence data from 2013 to 2022,and the model was applied to predict and verify the reported incidence data from January to June 2023.Results:A total of 2505 pulmonary tuberculosis patients were reported from 2013-2022 in Dongcheng,with an average annual reported incidence rate of 28.81/100 000.The highest reported incidence rate was in 2013(38.68/100 000,379 cases),and the lowest rate was in 2020(23.30/100 000,185 cases).The annually reported incidence rate showed an decreasing trend(x2trend=25.371,P<0.001),and the average annual decline rate was 5.26%.The highest detection rate of pathogenic positive pulmonary tuberculosis was in 2022(57.74%,97/168),and the lowest rate was in 2017(30.71%,74/241),showing an overall upward trend year by year(x2trend=29.945,P<0.001).The annual average reported incidence rate of male tuberculosis was 36.85/100 000(1559 cases),significantly higher than that of female tuberculosis(21.20/100 000,946 cases;x2=184.738,P<0.001;nmale∶nfemale=1.73∶1).The proportion of patients in the 20-29 age group(19.88%,498/2505)and retirees(37.72%,945/2505)was relatively high and the patients were mainly concentrated in Yongdingmenwai Street(11.38%,285/2505).Seasonal analysis showed that the seasonal index ranged from 0.83 to 1.09,with periodic fluctuations,and the epidemic period mainly concentrated from March to August,as well as in December.The SARIMA(0,1,2)(1,2,1)12 model fit well with the reported incidence trend(AIC=657.67),with an average relative error of-17.72%and high prediction accuracy(root mean square error of 5.188 and average absolute percentage error of 22.01%).Conclusion:From 2013 to 2022,the reported incidence of tuberculosis in Dongcheng District of Beijing showed a steady downward trend,and the patients were mainly male and retired population.Attention should be paid to the prevention and control of tuberculosis and propaganda and education of the elderly and young adults in spring and summer.The SARIMA(0,1,2)(1,2,1)12 model can well fit the trend of reported incidence of pulmonary tuberculosis in this region and has good predictive effects.
滕冲;王玉兰;刘柳;张芳;黄飞;李涛;赵冰;赵雁林;欧喜超
北京市东城区疾病预防控制中心,北京 100050传染病溯源预警与智能决策全国重点实验室中国疾病预防控制中心结核病预防控制中心,北京 102206
临床医学
结核,肺发病率模型,统计学预测
Tuberculosis,pulmonaryIncidenceModels,statisticalForecasting
《中国防痨杂志》 2024 (004)
397-402 / 6
国家重点研发计划(2022YFC2305204;2023YFC2307301) National Key Research and Development Program(2022YFC2305204;2023YFC2307301)
评论