[Epidemiological characteristics of active pulmonary tuberculosis and application of incidence prediction model in Xi'an from 2013 to 2023].

Q1 Medicine
W Shi, F Y Guo, L C Zeng, X Y Wang, Z S Jiang, Y F Wang
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引用次数: 0

Abstract

Objective: To analyze the epidemiological characteristics of active pulmonary tuberculosis (pulmonary tuberculosis) in Xi'an from 2013 to 2023 and predict the incidence trend of pulmonary tuberculosis in Xi'an by using autoregressive integrated moving average (ARIMA) product seasonal models to provide a decision-making basis for tuberculosis prevention and control. Methods: The incidence data of pulmonary tuberculosis reported in Xi'an from 2013 to 2023 were collected through the Tuberculosis Information Management System of the Chinese Center for Disease Control and Prevention. The Excel 2016 software was used for descriptive statistical analysis of pulmonary tuberculosis incidence data reported in Xi'an from 2013 to 2023. The SPSS 20.0 software was used to establish an ARIMA product seasonal model to predict the incidence of pulmonary tuberculosis in Xi'an. Results: A total of 49 860 cases of pulmonary tuberculosis were reported in Xi'an from 2013 to 2023, with an annual average incidence of 45.60/100 000. The incidence showed a downward trend in the past decade. The incidence was high in spring, with a peak from March to May, a small peak from November to January, and a low incidence in February and October. The annual average incidence of pulmonary tuberculosis in 2 suburban counties (52.80/100 000) was higher than that in 14 urban areas (43.21/100 000) (χ2=20.19, P<0.001). With the increase of age, the incidence of pulmonary tuberculosis was higher, and the incidence of the males was higher than that of female (χ2=378.34, P<0.001), the ratio of male to female incidence was 1.73∶1. The most occupation of the population was farmers, accounting for 46.54%. The established ARIMA (0, 1, 1) (1, 1, 1)12 product seasonal model exhibited a good prediction effect, with the Bayesian Information Criterion being -1.567, the root mean square error being 0.42, and the mean absolute percentage error being 9.62. The average relative error between the actual value and the predicted value was 6.63%, and the 95%CI of the predicted value included the actual value. Conclusions: 2013-2023, the incidence of pulmonary tuberculosis in Xi'an has been on the decline as a whole. Special attention should be paid to the prevention and control of tuberculosis in districts (counties) adjacent to mountainous areas in the south, people aged 60 years and above, and farmers and other vulnerable groups. The established ARIMA (0, 1, 1) (1, 1, 1)12 product seasonal model exhibited a good predictive effect and can be applied to the short-term prediction of tuberculosis incidence.

[2013 - 2023年西安市活动性肺结核流行病学特征及发病率预测模型的应用]。
目的:利用自回归综合移动平均(ARIMA)产品季节模型分析西安市2013 - 2023年活动性肺结核(pulmonary tuberculosis)的流行病学特征,预测西安市肺结核发病趋势,为结核病防治提供决策依据。方法:通过中国疾病预防控制中心结核病信息管理系统收集西安市2013 - 2023年报告的肺结核发病数据。采用Excel 2016软件对西安市2013 - 2023年报告的肺结核发病数据进行描述性统计分析。采用SPSS 20.0软件建立ARIMA产品季节模型对西安市肺结核发病率进行预测。结果:2013 - 2023年西安市共报告肺结核病例49 860例,年平均发病率为45.60/10万。近十年来发病率呈下降趋势。春季发病高发,3 - 5月为发病高峰,11 - 1月为小高峰,2月和10月发病低。2个城郊县肺结核年平均发病率(52.80/10万)高于14个城区(43.21/10万)(χ2=20.19, Pχ2=378.34), P12产品季节模型预测效果较好,贝叶斯信息标准为-1.567,均方根误差为0.42,平均绝对百分误差为9.62。实际值与预测值的平均相对误差为6.63%,预测值的95%CI包含了实际值。结论:2013-2023年,西安市肺结核发病率总体呈下降趋势。尤其要重视南方临近山区的区(县)、60岁及以上老年人、农民等弱势群体的结核病防治。建立的ARIMA(0,1,1)(1,1,1)12产品季节模型具有较好的预测效果,可用于结核病发病率的短期预测。
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来源期刊
中华流行病学杂志
中华流行病学杂志 Medicine-Medicine (all)
CiteScore
5.60
自引率
0.00%
发文量
8981
期刊介绍: Chinese Journal of Epidemiology, established in 1981, is an advanced academic periodical in epidemiology and related disciplines in China, which, according to the principle of integrating theory with practice, mainly reports the major progress in epidemiological research. The columns of the journal include commentary, expert forum, original article, field investigation, disease surveillance, laboratory research, clinical epidemiology, basic theory or method and review, etc.  The journal is included by more than ten major biomedical databases and index systems worldwide, such as been indexed in Scopus, PubMed/MEDLINE, PubMed Central (PMC), Europe PubMed Central, Embase, Chemical Abstract, Chinese Science and Technology Paper and Citation Database (CSTPCD), Chinese core journal essentials overview, Chinese Science Citation Database (CSCD) core database, Chinese Biological Medical Disc (CBMdisc), and Chinese Medical Citation Index (CMCI), etc. It is one of the core academic journals and carefully selected core journals in preventive and basic medicine in China.
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