佳木斯市2004-2017年流行性腮腺炎流行特征分析及趋势预测

陈欣; 吴晓敏; 包名家; 李明春; 王艳旭; 王雷; 薛晓峰; 王鹏; 王凯燕; 冯丽影

doi:10.16462/j.cnki.zhjbkz.2019.02.013

佳木斯市2004-2017年流行性腮腺炎流行特征分析及趋势预测

doi: 10.16462/j.cnki.zhjbkz.2019.02.013

154000 佳木斯, 佳木斯市疾病预防控制中心免疫规划科

详细信息

通讯作者:
包名家, E-mail: cmubmj@163.com

中图分类号: R512.1
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出版历程
- 收稿日期: 2018-08-19
- 修回日期: 2018-11-08
- 刊出日期: 2019-02-10

Epidemiological characteristics and trend prediction of mumps in Jiamusi city from 2004 to 2017

Department of Immunization Programmes, Jiamusi Center for Disease Control and Prevention, Jiamusi, HeiLong-jiang 154000, China

More Information

Corresponding author: BAO Ming-jia, E-mail: cmubmj@163.com

摘要

摘要: 目的分析佳木斯市流行性腮腺炎的流行特点，并对其发病趋势进行预测，为黑龙江省高寒地区采取有针对性的防控方法提供一定依据。方法通过传染病报告信息管理系统，收集佳木斯市2004-2017年报告的腮腺炎病例。选用描述流行病学方法，对其流行病学特点进行系统分析，并用自回归移动平均模型（autoregressive integrated moving average，ARIMA）对2018年腮腺炎的发病趋势进行预测。结果 2004-2017年佳木斯市腮腺炎共报告1 586例，年均发病率达到4.52/10万，近三年腮腺炎发病率出现上升趋势；男女发病率比为1.67∶1；病例主要集中在3~19岁，占全部病例的86.32%，5~9岁，10~14岁儿童发病率较高；发病有明显的季节性，每年的4-7月和11-次年1月为发病高峰；城区年发病率高于外郊县市区；ARIMA（4，1，2）（2，0，0）₁₂模型为相对最佳模型，预测的2018年1~6月腮腺炎发病率和实际值相符，预测2018年7~12月发病率为0.30/10万、0.35/10万、0.38/10万、0.39/10万、0.35/10万、0.33/10万。结论 ARIMA模型可以较为准确地预测佳木斯市腮腺炎发病趋势，为有效降低儿童发病率，建议在儿童学龄前阶段（3~6岁）或小学阶段开展第二剂次的腮腺炎疫苗接种，同时应继续做好托幼机构等集体单位的疫情监测防控工作。
- 流行性腮腺炎 /
- 流行特征 /
- 趋势预测
Abstract: Objective To analyze the epidemiological characteristics of mumps in Jiamusi city, and predict the incidence trend, so as to provide evidence for taking targeted prevention and control measures in the cold areas in Heilongjiang Province. Methods The mumps cases were collected from China Information System for Disease Control and Prevention in Jiamusi city from 2004 to 2017.Descriptive epidemiologic method was used for analyzing the epidemic of mumps in Jiamusi city during 2004-2017, and the autoregressive integrated moving average (ARIMA) was used to forecast the incidence of mumps in 2018. Results A total of 1 586 cases of mumps were reported in Jiamusi city during 2004-2017, the average annual incidence rate was 4.52/100 000. The incidence of mumps increased year by year from 2015 to 2017.The ratio of male to female was 1.67:1, those aged from 3 to 19 years accounted for 86.32% of the total cases, the higher incidence rates were found at the age of 5-9 and 10-14 years.The incidence of mumps presented obviously seasonal characteristics.Most cases concentrated from April to July and from November to January. The incidence of urban disease was higher than that of other counties; The established finally mode was ARIMA(4, 1, 2)(2, 0, 0)₁₂ and the predicted incidence from January 2018 to June 2018 was consistent with the actual one.From July 2018 to December 2018, predictive mumps incidence were: 0.30/100 000, 0.35/100 000, 0.38/100 000, 0.39/100 000, 0.35/100 000, 0.33/100 000. Conclusions ARIMA model could predict the trend of mumps in Jiamusi city.To reduce the incidence of children, it is recommended to develop a second dose of mumps vaccine at the preschool age (3-6 years) or primary school; At the same time, surveillance and control should be continually strengthened in kindergartens and schools.
- Mumps /
- Epidemiological characteristics /
- trend prediction

HTML全文

图 1 2004-2017年佳木斯市流行性腮腺炎发病情况

Figure 1. Incidence of mumps in Jiamusi city from 2004 to 2017

下载: 全尺寸图片幻灯片

图 2 2004-2017年佳木斯市流行性腮腺炎的发病时间分布

Figure 2. Time distribution of mumps epidemic in Jiamusi city from 2004 to 2017

下载: 全尺寸图片幻灯片

图 3 2004-2017年佳木斯市流行性腮腺炎发病年龄分布情况

Figure 3. Age distribution of mumps in Jiamusi city from 2004 to 2017

下载: 全尺寸图片幻灯片

图 4 2018年佳木斯市流行性腮腺炎发病率预测

Figure 4. Incidence prediction of mumps epidemic in Jiamusi city in 2018

下载: 全尺寸图片幻灯片

表 1 ARIMA模型组合结果

Table 1. Results of ARIMA model combination

组合结果	AIC
ARIMA(4，1，0)(0，1，0)₁₂	122.66
ARIMA(4，1，0)(0，1，1)₁₂	39.47
ARIMA(4，1，0)(0，1，2)₁₂	38.19
ARIMA(4，1，0)(1，1，0)₁₂	73.67
ARIMA(4，1，0)(1，1，1)₁₂	38.86
ARIMA(4，1，0)(1，1，2)₁₂	无法拟合
ARIMA(4，1，0)(2，1，0)₁₂	40.15
ARIMA(4，1，0)(2，1，1)₁₂	37.65
ARIMA(4，1，0)(2，1，2)₁₂	39.47
ARIMA(4，1，2)(2，0，0)₁₂	20.93

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表 2 佳木斯市2018年1月~6月流行性腮腺炎月发病率和预测值比较

Table 2. Comparison of monthly incidence and predicted value of mumps in Jiamusi city from January 2018 to June 2018

时间	实际值(/10万)	预测值(/10万)	95% CI下限	95% CI上限	绝对误差	相对误差
2018年1月	0.25	0.31	0.00	0.93	0.06	24.00
2018年2月	0.29	0.36	0.04	1.02	0.07	24.14
2018年3月	0.38	0.42	0.22	1.20	0.04	10.53
2018年4月	0.53	0.60	0.16	1.14	0.07	13.21
2018年5月	0.49	0.54	0.06	1.10	0.05	10.20
2018年6月	0.41	0.47	0.01	0.79	0.06	14.63
均值					0.06	16.12

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参考文献(25)

[1]	李兰娟, 任红. 传染病学[M]. 第8版. 北京: 人民卫生出版社, 2013, 73-76. Li LJ, Ren H. Epidemiology[M]. The eighth edition. Beijing: People's Medical Publishing House, 2013.
[2]	钟贵良, 林希建, 刘姝. 2008-2012年长沙市流行性腮腺炎流行病学特征分析[J]. 中华疾病控制杂志, 2014, 18(2): 120-122. http://zhjbkz.ahmu.edu.cn/article/id/JBKZ201402009 Zhong GL, Lin XJ, Liu S. Analysis on epidemiological characteristics of mumps in Changsha City from 2008 to 2012[J]. Chin J Dis Control Prev, 2014, 18(2): 120-122. http://zhjbkz.ahmu.edu.cn/article/id/JBKZ201402009
[3]	沈忠周, 王雅文, 马帅, 等. ARIMA模型在预测我国乙肝月报告发病数中的应用[J]. 中华疾病控制杂志, 2018, 22(3): 298-301, 307. DOI: 10.16462/j.cnki.zhjbkz.2018.03.019. Shen ZZ, Wang YW, Ma S, et al. Prediction on the number of hepatitis B by ARIMA model in China[J]. Chin J Dis Control Prev, 2018, 22(3): 298-301, 307. DOI: 10.16462/j.cnki.zhjbkz.2018.03.019.
[4]	Zheng YL, Zhang LP, Zhang XL, et al. Forecast model analysis for the morbidity of tuberculosis in Xinjiang, China[J]. PLoS One, 2015, 10(3): e0116832. DOI:10.1371/journal.pone.0116832.eCollection 2015.
[5]	郑莉, 李宁, 唐险峰, 等. 湖北省2005-2015年流行性腮腺炎流行病学特征分析[J]. 中国疫苗和免疫, 2016, 22(3): 263-266, 251. DOI: 10.3784/j.issn.1003-9961.2016.08.010. Zheng L, Li N, Tang XF, et al. Epidemiological characteristics of mumps in Hubei province from 2005 to 2015[J]. Chinese Journal of Vaccines and Immunization, 2016, 22(3): 263-266, 251. DOI: 10.3784/j.issn.1003-9961.2016.08.010.
[6]	刘强林, 加永卓玛, 尼玛卓玛, 等. 2005-2014年西藏山南地区流行性腮腺炎流行病学分析[J]. 现代预防医学, 2018, 45(6): 974-976. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201806004.htm Liu QL, Jia YZM, Ni MZM, et al. Analysis of the epidemiological characteristics of mumps in Shannan area of Tibet from 2005 to 2014[J]. Modern Preventive Medicine, 2018, 45(6): 974-976. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201806004.htm
[7]	李澄, 田晓灵, 李彬, 等. 内蒙古2005-2014年流行性腮腺炎流行病学特征分析[J]. 中国疫苗和免疫, 2016, 22(1): 30-33. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGJM201601007.htm Li C, Tian XL, Li B, et al. Analysis of the epidemiological characteristics of mumps in inner Mongolia from 2005 to 2014[J]. Chinese Journal of Vaccines and Immunization, 2016, 22(1): 30-33. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGJM201601007.htm
[8]	郭立春, 刘慧慧, 周剑惠, 等. 吉林省2005-2014年流行性腮腺炎流行特征分析[J]. 中国热带医学, 2016, 16(7): 695-697. DOI: 10.13604/j.cnki.46-1064/r.2016.07.18 Guo LC, Liu HH, Zhou JH, et al. Analysis of epidemiological characteristics of mumps in Jilin province from 2005 to 2014[J]. China Tropical Medicine, 2016, 16(7): 695-697. DOI: 10.13604/j.cnki.46-1064/r.2016.07.18
[9]	张建, 杨菁菁, 刘方. 北京市朝阳区2011-2015年流行性腮腺炎流行病学特征分析[J]. 中国生物制品学杂志, 2017, 30(5): 514-518. DOI: 10.13200/j.cnki.cjb.001737 Zhang J, Yang JJ, Liu F. Epidemiological characteristics of mumps in Chaoyang District, Beijing City, China in 2011-2015[J]. Chin J Biologicals, 2017, 30(5): 514-518. DOI: 10.13200/j.cnki.cjb.001737
[10]	苏琪茹, 刘隽, 马超, 等. 2004-2013年中国流行性腮腺炎流行病学特征分析[J]. 中华预防医学杂志, 2016, 50(7): 611-614. DOI: 10.3760.cma.j.issn.0253-9624.2016.07.009 Su QR, Liu J, Ma C, et al. Epidemic profile of mumps in China during 2004-2013[J]. Chin J Prev Med, 2016, 5(7): 611-614. DOI: 10.3760.cma.j.issn.0253-9624.2016.07.009
[11]	唐丽, 胡锦流. 2006-2015年江苏淮安市腮腺炎流行十年回顾性分析[J]. 公共卫生与预防医学, 2017, 28(2): 32-34, 1006-2483. https://www.cnki.com.cn/Article/CJFDTOTAL-FBYF201702009.htm Tang L, Hu JL. Retrospective analysis of mumps epidemic in Huaian City in Jiangsu Province from 2006 to 2015[J]. J of Pub Health and Prev Med, 2017, 28(2): 32-34, 1006-2483. https://www.cnki.com.cn/Article/CJFDTOTAL-FBYF201702009.htm
[12]	傅传喜, 杨琼英, 杨智聪, 等. 气象因子与流行性腮腺炎发病关联的时间序列研究[J]. 华南预防医学, 2014, 40(4): 306-311. DOI: 10.13217/j.scjpm.2014.0306 Fu CX, Yang QY, Yang ZC, et al. Time series study of relationship between meteorological factors and mumps incidence[J]. South China J Prev Med, 2014, 40(4): 306-311. DOI: 10.13217/j.scjpm.2014.0306
[13]	黎沙, 杜进发, 钟革, 等. 2005-2015年广西流行性腮腺炎流行病学特征分析[J]. 应用预防医学, 2017, 23(5): 392-394. DOI: 10.3969/j.issn.1673-758X.2017.05.013 Li S, Du JF, Zhong G, et al. Analysis of epidemiological characteristics of mumps in Guangxi from 2005 to 2015[J]. J Applied Prev Med, 2017, 23(5): 392-394. DOI: 10.3969/j.issn.1673-758X.2017.05.013
[14]	李小燕, 赵勇, 凌娟, 等. 2004-2016年重庆市江北区流行性腮腺炎流行病学特征分析[J]. 中国病毒学杂志, 2018, 8(1): 58-61. DOI: 10.16505/j.2095-0136.2018.0018 Li XY, Zhao Y, Ling J, et al. Epidemiological characteristics of mumps from 2004 to 2016 in Jiangbei district of Chongqing, China[J]. Chin J Viral Dis, 2018, 8(1): 58-61. DOI: 10.16505/j.2095-0136.2018.0018
[15]	张松杰, 马倩倩, 黄莹等. 西安市小学传染病流行/暴发现况及相关影响因素调查研究[J]. 中华疾病控制杂志, 2018, 22(3): 262-265. DOI: 10.16462/j.cnki.zhjbkz.2018.03.012 Zhang SJ, Ma QQ, Huang Y, et al. Investigation on status of infectious diseases epidemics or outbreaks and related factors in primary schools in Xi'an[J]. Chin J Dis Control Prev, 2018, 22(3): 262-265. DOI: 10.16462/j.cnki.zhjbkz.2018.03.012
[16]	戴孟阳, 张春青, 王东, 等. 2013-2017年沈阳市流行性腮腺炎流行病学特征分析[J]. 预防医学论坛, 2018, 24(8): 617-619. DOI: 10.16406/j.pmt.issn.1672-9153.2018.08.001 Dai MY, Zhang CQ, Wang D, et al. Analysis on epidemiological characteristics of mumps, Shenyang city, 2013-2017[J]. Prev Med Trib, 2018, 24(8): 617-619. DOI: 10.16406/j.pmt.issn.1672-9153.2018.08.001
[17]	McLean HQ, Fiebelkorn AP, Temte JL, et al. Prevention of measles, rubella, congenital rubella syndrome, and mumps, 2013: summary of recommendations of the advisory committee on immunization practices (ACIP)[J]. MMWR Recomm Rep, 2015, 64[9]: 259.
[18]	徐虹, 李岩, 范晨璐, 等. 2007-2016年哈尔滨市流行性腮腺炎流行病学特征分析[J]. 现代预防医学, 2018, 45(17): 3076-3079. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201817002.htm Xu H, Li Y, Fan CL, et al. Epidemiological analysis of mumps in Harbin, 2007-2016[J]. Modern Preventive Medicine, 2018, 45(17): 3076-3079. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201817002.htm
[19]	Olsson GE, Hjertqvist M, Lundkvist A, et al. Predicting high risk for human hantavirus infections, Sweden[J]. Emerg Infect Dis, 2009, 15(1): 104-106. DOI: 10.3201/eid1501.080502.
[20]	周其宏, 冯晓明, 汪银等. 皖南山区流行性腮腺炎发病趋势的智能预测模型[J]. 中华疾病控制杂志, 2010, 14(8): 739-741. http://zhjbkz.ahmu.edu.cn/article/id/JBKZ201008018 Zhou QH, Feng XM, Wang Y, et al. A forecast model study on the incidence of mumps in southern Anhui Province[J]. Chin J Dis Control Prev, 2010, 14(8): 739-741. http://zhjbkz.ahmu.edu.cn/article/id/JBKZ201008018
[21]	柳林, 刘继锋. 西安市2007-2016年流行性腮腺炎流行病学分析及发病趋势预测[J]. 国外医学(医学地理分册), 2017, 38(3): 222-224, 227. DOI: 10.3969/j.issn.1001-8883.2017.03.004 Liu L, Liu JF. Epidemiology and forecasting of mumps in Xi'an, 2007-2016[J]. Foreign Medical Science Section of Medgeography, 2017, 38(3): 222-224, 227. DOI: 10.3969/j.issn.1001-8883.2017.03.004
[22]	Gharbi M, Quenel P, Gustave J, et al. Time series analysis of dengue incidence in Guadeloupe, French West Indies: forecasting models using climate variables as Predictors[J]. BMC Infect Dis, 2011, 11: 166. DOI: 10.1186/1471-2334-11-166.
[23]	Rasmussen SS, Johansen NB, Witte DR, et al. Incidence of register-based diabetes 10 years after a stepwise diabetes screening programme: the ADDITION-Denmark study[J]. Diabetologia 2016, 59(5): 989-997. DOI: 10.1007/s00125-016-3887-6.
[24]	Zia UQ, Hassan S, Khan GM. Adaptive resource utilization prediction system for infrastructure as a Service Cloud[J]. Comput Intell Neurosci, 2017: 4873459. DOI: 10.1155/2017/4873459.
[25]	杨小兵, 汪鹏, 江高峰. ARIMA乘积季节模型在流行性腮腺炎发病率预测中的应用[J]. 公共卫生与预防医学, 2013, 24(6): 39-42. https://www.cnki.com.cn/Article/CJFDTOTAL-FBYF201306013.htm Yang XB, Wang P, Jiang GF. The mumps incidence prediction by multiple seasonal ARIMA model[J]. J of Pub Hea and Pre Med, 2013, 24(6): 39-42 https://www.cnki.com.cn/Article/CJFDTOTAL-FBYF201306013.htm