Analysis of tuberculosis epidemiological characteristics and application of incidence prediction model in Fujian Province from 2010 to 2019

LIN Shu-fang; ZHOU Yin-fa; ZHANG Shan-ying; DAI Zhi-song; CHEN Dai-quan

doi:10.16462/j.cnki.zhjbkz.2021.07.006

Volume 25 Issue 7

Aug. 2021

Turn off MathJax

Article Contents

Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2021 > 25(7): 768-774

LIN Shu-fang, ZHOU Yin-fa, ZHANG Shan-ying, DAI Zhi-song, CHEN Dai-quan. Analysis of tuberculosis epidemiological characteristics and application of incidence prediction model in Fujian Province from 2010 to 2019[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(7): 768-774. doi: 10.16462/j.cnki.zhjbkz.2021.07.006

Citation:

LIN Shu-fang, ZHOU Yin-fa, ZHANG Shan-ying, DAI Zhi-song, CHEN Dai-quan. Analysis of tuberculosis epidemiological characteristics and application of incidence prediction model in Fujian Province from 2010 to 2019[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(7): 768-774. doi: 10.16462/j.cnki.zhjbkz.2021.07.006

Citation:

LIN Shu-fang, ZHOU Yin-fa, ZHANG Shan-ying, DAI Zhi-song, CHEN Dai-quan. Analysis of tuberculosis epidemiological characteristics and application of incidence prediction model in Fujian Province from 2010 to 2019[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(7): 768-774. doi: 10.16462/j.cnki.zhjbkz.2021.07.006

PDF( 3894 KB)

Analysis of tuberculosis epidemiological characteristics and application of incidence prediction model in Fujian Province from 2010 to 2019

doi: 10.16462/j.cnki.zhjbkz.2021.07.006

Department of Tuberculosis Prevention and Control, Fujian Center for Disease Control and Prevention, Fuzhou 350001, China

Funds:

Construction of Fujian Provincial Scientific and Technological Innovation Platform 2019Y2001

More Information

Corresponding author: LIN Shu-fang, E-mail: zqszl@163.com
Received Date: 2020-09-25
Rev Recd Date: 2021-01-13

Available Online: 2021-08-13

Publish Date: 2021-07-10

Abstract

Abstract

Objective The study aims to analyze the epidemiological characteristics of tuberculosis (TB) in Fujian Province from 2010 to 2019, and establishing autoregressive integrated moving average (ARIMA) model to discuss its application in predicting the monthly incidence of TB in Fujian Province. Methods The incidence data of active TB reported in Fujian Province from January 2010 to June 2020 were obtained through the TB Information Management System of Chinese Center for Disease Control and Prevention. The Excel 2016, ArcGIS 10.2 and SPSS 24.0 softwares were used to describe the epidemiological characteristics of TB in Fujian Province from 2010 to 2019, and established the composite seasonal ARIMA model to predict the monthly incidence of TB. Results A total of 202 842 cases of active TB were reported in Fujian Province from 2010 to 2019, with an average incidence of 53.5/100 000, and the incidence showed a decreasing trend in the past decade (χ²=1 952.427, P < 0.001). Relatively few cases were reported in January, February and October, accounting for 7.1%, 6.2% and 7.6%, and there was a small peak in March, accounting for 9.2%. The incidence of TB reported in coastal city was significantly higher than that in inland area (χ²=1 169.414, P < 0.001). The number of male patients with active TB was 2.77 times than that of female patients. The incidence of TB increased with age, and reached the highest at the age of 65 to 75; and the patients were mainly in the middle and young ages, accounting for 81.5%. The proportion of patients with migrant workers was the highest, accounting for 59.9%, followed by housework and unemployment, accounting for 16.4%. The desirable prediction result obtained by ARIMA (3, 1, 2) (0, 1, 1)₁₂, showed that the relative error was 2.4% and 95% confidence interval of the predicted value of each month contained the actual value. Conclusion The incidence of TB in Fujian Province presented a declining trend in the past decade. Male, young adult and migrant workers were the important population for TB control in Fujian Province. The composite seasonal ARIMA (3, 1, 2) (0, 1, 1)₁₂ model can be used for predicting the short-term incidence of TB in Fujian Province.
- Tuberculosis,
- Pulmonary,
- Epidemiologic characteristics,
- Prediction,
- ARIMA model

FullText(HTML)

References(22)

References

[1]	中华人民共和国国家卫生健康委员会. 2019年全国法定传染病疫情概况[EB/OL]. (2020-04-20)[2020-08-14]. http://www.nhc.gov.cn/jkj/s3578/202004/b1519e1bc1a944fc8ec176db600f68d1.shtml. National Health Commission of the People's Republic of China. General situation of notifiable infectious diseases in China in 2019[EB/OL]. (2020-04-20)[2020-08-14]. http://www.nhc.gov.cn/jkj/s3578/202004/b1519e1bc1a944fc8ec176db600f68d1.shtml.
[2]	World Health Organization. 2019 Global tuberculosis report[R]. Geneva: World Health Organization, 2019: 38-39.
[3]	刘健雄, 钟球. "终止结核病"面临的挑战与应对策略[J]. 中国防痨杂志, 2020, 42(4): 308-310. DOI: 10.3969/j.issn.1000-6621.2020.04.002. Liu JX, Zhong Q. "challenges and countermeasures of ending tuberculosis"[J]. Chin J Antituberc, 2020, 42(4): 308-310. DOI: 10.3969/j.issn.1000-6621.2020.04.002.
[4]	孙振球. 医学统计学[M]. 北京: 人民卫生出版社, 2010. Sun ZQ. Medical statistics[M]. Beijing: People's Medical Publishing House, 2010.
[5]	易静, 杜昌廷, 王润华, 等. 自回归求和移动平均季节乘积模型在结核病发病率预测中的应用[J]. 中华预防医学杂志, 2007, 41(2): 118-121. DOI: 10.3760/j.issn:0253-9624.2007.02.009. Yi J, Du CT, Wang RH, et al. Applications of multiple seasonal autoregressive integrated moving average (ARIMA) model on predictive incidence of tuberculosis[J]. Chin J Prev Med, 2007, 41(2): 118-121. DOI: 10.3760/j.issn:0253-9624.2007.02.009.
[6]	张文彤, 董伟. 统计分析高级教程[M]. 北京: 高等教育出版社, 2013. Zhang WT, Dong W. Advanced course of statistical analysis[M]. Beijing: Higher Education Press, 2013.
[7]	王燕. 应用时间序列分析[M]. 北京: 中国人民大学出版社, 2015. Wang Y. Application of time series analysis[M]. Beijing: China Renmin University Press, 2015.
[8]	刘丽珺, 刘宇, 周兴余, 等. 四川省2008-2018年流行性乙型脑炎流行特征及ARIMA模型应用[J]. 中华疾病控制杂志, 2019, 23(8): 916-921. DOI: 10.16462/j.cnki.zhjbkz.2019.08.007. Liu LJ, Liu Y, Zhou XY, et al. Analysis of epidemiological characteristics of Japanese encephalitis in Sichuan Province from 2008 to 2018 and application of autoregressive integrated moving average model[J]. Chin J Dis Control Prev, 2019, 23(8): 916-921. DOI: 10.16462/j.cnki.zhjbkz.2019.08.007.
[9]	王晓君, 李月华, 易凤莲, 等. 1990-2017年中国结核病流行与控制情况[J]. 中华流行病学杂志, 2020, 41(6): 856-860. DOI: 10.3760/cma.j.cn112338-20190809-00587. Wang XJ, Li YH, Yi FL, et al. Description of epidemic features and control status on tuberculosis in China, 1990-2017[J]. Chin J Epidemiol, 2020, 41(6): 856-860. DOI: 10.3760/cma.j.cn112338-20190809-00587.
[10]	张根友, 王纪祥, 邹铮, 等. 2005-2012年安徽省结核病流行特征分析[J]. 中华疾病控制杂志, 2014, 18(6): 504-507. https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ201406008.htm Zhang GY, Wang JX, Zou Z, et al. Analysis on the epidemiological characteristics of tuberculosis in Anhui Province, 2005-2012[J]. Chin J Dis Control Prev, 2014, 18(6): 504-507. https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ201406008.htm
[11]	黄玉, 钟节鸣, 陈彬, 等. 2010年浙江省结核病发病流行病学特征分析[J]. 疾病监测, 2011, 26(8): 601-603. DOI: 10.3784/j.issn.1003-9961.2011.08.005. Huang Y, Zhong JM, Chen B, et al. Epidemiological characteristics of tuberculosis in Zhejiang Province, 2010[J]. Dis Surveillance, 2011, 26(8): 601-603. DOI: 10.3784/j.issn.1003-9961.2011.08.005.
[12]	毛宁, 梁爽, 何琳, 等. 2009-2014年辽宁省结核病流行性特征分析[J]. 中华疾病控制杂志, 2017, 21(3): 287-290. DOI: 10.16462/j.cnki.zhjbkz.2017.03.017. Mao N, Liang S, He L, et al. Analysis on the epidemiological characteristics of tuberculosis in Liaoning Province, 2009-2014[J]. Chin J Dis Control Prev, 2017, 21(3): 287-290. DOI: 10.16462/j.cnki.zhjbkz.2017.03.017.
[13]	陈伟, 王雪静, 王黎霞, 等. 全国五省结核病与性别关系的研究[J]. 中国防痨杂志, 2010, 32(9): 534-539. https://www.cnki.com.cn/Article/CJFDTOTAL-ZFLZ201009017.htm Chen W, Wang XJ, Wang LX, et al. TB and Gender in five provinces of China[J]. Chin J Antituberc, 2010, 32(9): 534-539. https://www.cnki.com.cn/Article/CJFDTOTAL-ZFLZ201009017.htm
[14]	杨本付, 綦斐. 吸烟与结核病关系的Meta分析[J]. 中华行为医学与脑科学杂志, 2010, 19(11): 1025-1028. DOI: 10.3760/cma.j.issn.1674-6554.2010.11.024. Yang BF, Qi F. A meta-analysis on the association between smoking and tuberculosis[J]. Chin J Behav Med Brain Sci, 2010, 19(11): 1025-1028. DOI: 10.3760/cma.j.issn.1674-6554.2010.11.024.
[15]	吴妍, 李琦. 老年肺结核的诊治现状与进展[J]. 中国防痨杂志, 2015, 37(9): 975-978. DOI: 10.3969/j.issn.1000-6621.2015.05.012. Wu Y, Li Q. The status and progress of diagnosis and treatment for elderly patients with tuberculosis[J]. Chin J Antituberc, 2015, 37(9): 975-978. DOI: 10.3969/j.issn.1000-6621.2015.09.012.
[16]	袁莺楹, 董建成. 基于数学模型的疾病预测方法比较研究[J]. 软件导刊, 2009, 8(5): 108-110. https://www.cnki.com.cn/Article/CJFDTOTAL-RJDK200905047.htm Yuan YY, Dong JC. Comparative study on disease prediction methods based on mathematical model[J]. Software Guide, 2009, 8(5): 108-110. https://www.cnki.com.cn/Article/CJFDTOTAL-RJDK200905047.htm
[17]	沈忠周, 马帅, 曲翌敏, 等. ARIMA模型在我国法定传染病报告数中的应用[J]. 中华流行病学杂志, 2017, 38(12): 1708-1712. DOI: 10.3760/cma.j.issn.0254-6450.2017.12.025. Shen ZZ, Ma S, Qu YM, et al. Application of autoregressive integrated moving average model in predicting the reported notifiable communicable diseases in China[J]. Chin J Epidemiol, 2017, 38(12): 1708-1712. DOI: 10.3760/cma.j.issn.0254-6450.2017.12.025.
[18]	付志勇, 陈秋萍, 陈田木, 等. ARIMA模型在肺结核疫情预测中的应用[J]. 热带医学杂志, 2011, 11(12): 1350-1353. doi: 10.3969/j.issn.1672-3619.2011.12.003 Fu ZY, Chen QP, Chen TM, et al. Application of ARIMA model in the predition of tuberculosis[J]. J Trop Med, 2011, 11(12): 1350-1353. doi: 10.3969/j.issn.1672-3619.2011.12.003
[19]	钟球, 蒋莉, 周琳, 等. 广东省结核病发病趋势的时间序列分析[J]. 中国防痨杂志, 2010, 32(9): 515-519. https://www.cnki.com.cn/Article/CJFDTOTAL-ZFLZ201009012.htm Zhong Q, Jiang L, Zhou L, et al. Application of time series analysis for the prediction of incidence trend of tuberculosis in Guangdong Province[J]. Chin J Antituberc, 2010, 32(9): 515-519. https://www.cnki.com.cn/Article/CJFDTOTAL-ZFLZ201009012.htm
[20]	言晨绮, 王瑞白, 刘海灿, 等. ARIMA模型预测2018-2019年我国肺结核发病趋势的应用[J]. 中华流行病学杂志, 2019, 40(6): 633-637. DOI: 10.360/cma.j.issn.0254-6450.2019.06.006. Yan CQ, Wang RB, Liu HC, et al. Application of ARIMA model in predicting the incidence of tuberculosis in China from 2018 to 2019[J]. Chin J Epidemiol, 2019, 40(6): 633-637. DOI: 10.360/cma.j.issn.0254-06450.2019.06.006.
[21]	闫银锁, 孙闪华, 李亚敏, 等. 差分自回归移动平均模型与Elman神经网络及其组合模型对北京市肺结核发病预测效果的比较[J]. 中国防痨杂志, 2019, 41(6): 669-675. DOI: 10.3969/j.issn.1000-6621.2019.06.014. Yan YS, Sun SH, Li YM, et al. Comparison of ARIMA model and Elman neural network along with ARIMA-Elman combination model in predicting incidence of tuberculosis in Beijing[J]. Chin J Antituberc, 2019, 41(6): 669-675. DOI: 10.3969/j.issn.1000-6621.2019.06.014.
[22]	周惠, 陈晓军, 张杨, 等. ARIMA模型在肺结核登记病例数预测中的应用[J]. 江苏预防医学, 2018, 29(3): 286-288. DOI: 10.13668/j.issn.1006-9070.2018.03.016. Zhou H, Chen XJ, Zhang Y, et al. Application of ARIMA model in predicting the number of registered tuberculosis[J]. Jiangsu J Prev Med, 2018, 29(3): 286-288. DOI: 10.13668/j.issn.1006-9070.2018.03.016.