2010-2018年湖北省猩红热流行病学特征及发病趋势预测

蔡晶; 黄淑琼; 杨雯雯; 张鹏; 谢聪; 吴然

doi:10.16462/j.cnki.zhjbkz.2020.02.003

2010-2018年湖北省猩红热流行病学特征及发病趋势预测

doi: 10.16462/j.cnki.zhjbkz.2020.02.003

430079 武汉, 湖北省疾病预防控制中心预防医学信息研究所

基金项目: 湖北省卫生计生委面上项目(WJ2017M139)

详细信息

通讯作者:
黄淑琼, Email:48501247@qq.com

中图分类号: R515.1;R181
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- 被引次数: 0
出版历程
- 收稿日期: 2019-08-15
- 修回日期: 2019-12-04
- 刊出日期: 2020-02-10

Epidemiological characteristics and trend prediction of scarlet fever in Hubei Province from 2010 to 2018

Institute of Preventive Medicine Information, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China

Funds: Project of Hubei Provincial Health and Family Planning Commission(WJ2017M139)

More Information

Corresponding author: HUANG Shu-qiong, Email:48501247@qq.com

摘要

摘要: 目的分析猩红热的流行病学特征, 预测其发病趋势, 为猩红热防控策略的制定提供参考依据。方法采用Spearman相关分析、聚类分析、季节指数模型和季节ARIMA模型进行分析和预测。结果 2010-2018年猩红热年均发病率为1.37/10万, 年发病率与年份存在正相关关系(r_s=0.817, P=0.007);4-6月和11-12月为高发月份; 聚类分析具有统计学意义(F=4795.30, P < 0.001), 高发地区为神农架林区、宜昌市、恩施州、武汉市; 报告病例集中在1~14岁, 以学生、幼托儿童和散居儿童为主, 男性发病率高于女性; 拟合的最优模型为自回归积分滑动平均模型(auto-regressive integrated moving average, ARIMA)(0, 1, 1)(0, 1, 0)₁₂, 预测显示2019年月度发病特征与历年一致, 年发病率为10.22/10万(95% CI:2.33/10万~30.43/10万), 较2018年发病水平上升。结论 2010-2018年湖北省猩红热发病水平整体呈上升趋势; 发病呈双峰特征, 以学生为主要发病群体, 男性高于女性, 发病主要集中在鄂西南等山区和省会城市; ARIMA模型在猩红热发病趋势预测中具有较好的适用性, 2019年发病水平会持续上升, 需结合流行特征加强监测和防控。
- 猩红热 /
- 湖北省 /
- 流行特征 /
- 发病趋势
Abstract: Objective To provide reference for formulating scarlet fever prevention and control strategies by analyzing the epidemiological characteristics and predicting the incidence trend of scarlet fever. Methods Spearman correlation analysis, clustering analysis, seasonal index model and seasonal ARIMA model were used for analysis and prediction. Results The average annual incidence of scarlet fever in 2010-2018 was 1.37/100 000, and there was a positive correlation between annual incidence and year(r_s=0.817, P=0.007). April-June and November-December were high incidence months. The clustering analysis was significant(F=4795.30, P < 0.001), showing that the high-incidence areas are Shennongjia, Yichang, Enshi, Wuhan. Reported cases were concentrated in 1-14 years old, mainly for students, child care children and scattered children. The incidence rate of males was higher than that of females. The optimal model is ARIMA(0, 1, 1)(0, 1, 0)₁₂. The prediction showed that the monthly incidence characteristics of 2019 were consistent with previous years, and the annual incidence rate was 10.22/100 000(95% CI:2.33/100 000-30.43/100 000), which was higher than the incidence of 2018. Conclusions The incidence of scarlet fever in Hubei Province is generally on the rise from 2010 to 2018. The incidence is bimodal. Students are the main disease group. The incidence rate of males is higher. The incidence is mainly concentrated in the mountainous areas of southwest and capital cities. The ARIMA model has a good applicability in the prediction of scarlet fever. The incidence level will continue to rise in 2019, and it is necessary to strengthen monitoring and control measures with reference to epidemiological characteristics.
- Scarlet fever /
- Hubei Province /
- Epidemiological characteristics /
- Incidence trend

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图 1 2010-2018年湖北省猩红热月发病率

Figure 1. Monthly incidence of scarlet fever in Hubei Province from 2010 to 2018

下载: 全尺寸图片幻灯片

图 2 原始数据序列ACF和PACF图

Figure 2. ACF and PACF diagrams of the original data sequence

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图 3 经差分处理后数据序列ACF和PACF图

Figure 3. ACF and PACF diagrams of the data sequence after differential processing

下载: 全尺寸图片幻灯片

表 1 2010-2018年各月份季节指数及调整季节指数

Table 1. Monthly seasonal index and adjusted seasonal index from 2010 to 2018

月份	季节指数(S)								调整季节指数(St)
月份	2010	2011	2012	2013	2014	2015	2016	2017	调整季节指数(St)
1	0.50	0.73	1.02	0.60	0.82	2.14	1.90	0.57	1.10
2	0.24	0.54	1.00	0.36	0.30	0.71	0.63	0.56	0.54
3	0.47	1.05	1.68	0.82	0.80	0.87	1.09	0.77	0.97
4	0.69	2.07	1.79	0.92	0.79	1.56	1.38	0.97	1.31
5	1.11	3.21	1.76	0.91	1.07	1.97	1.98	1.44	1.72
6	0.65	3.14	1.20	0.78	1.64	1.69	1.59	1.36	1.53
7	0.42	0.97	0.66	0.44	0.76	0.92	0.60	0.61	0.68
8	0.41	0.64	0.26	0.22	0.19	0.42	0.44	0.40	0.37
9	0.60	0.47	0.38	0.22	0.37	0.66	0.51	0.33	0.46
10	0.39	1.23	0.38	0.43	0.46	1.22	0.58	0.40	0.67
11	0.96	2.11	0.87	0.63	0.91	1.77	1.30	1.31	1.22
12	1.50	2.81	0.97	1.04	1.53	2.63	1.15	1.36	1.66

下载: 导出CSV

表 2 两种模型预测效果比较

Table 2. Comparison of prediction effects of the two models

月份	实际值(/10万)	季节指数模型		季节ARIMA模型
月份	实际值(/10万)	预测值(/10万)	相对误差(%)	预测值(/10万)	相对误差(%)
1	0.15	0.15	0.00	0.10	-33.33
2	0.06	0.07	16.67	0.10	66.67
3	0.11	0.13	18.18	0.14	27.27
4	0.27	0.18	-33.33	0.18	-33.33
5	0.37	0.24	-35.14	0.27	-27.03
6	0.36	0.22	-38.89	0.27	-25.00
7	0.17	0.10	-41.18	0.12	-29.41
8	0.08	0.05	-37.50	0.08	0.00
9	0.10	0.07	-30.00	0.07	-30.00
10	0.21	0.10	-52.38	0.09	-57.14
11	0.50	0.18	-64.00	0.29	-42.00
12	0.63	0.24	-61.90	0.31	-50.79

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