上海市2005--20 1 2年猩红热流行特征和发病趋势分析

任宏; 王晔; 陈明亮; 袁政安; 李燕婷; 黄埔; 胡家瑜

Abstract

任宏,王晔,陈明亮,袁政安,李燕婷,黄埔,胡家瑜.上海市2005--20 1 2年猩红热流行特征和发病趋势分析[J].Chinese journal of Epidemiology,2013,34(7):706-710

上海市2005--20 1 2年猩红热流行特征和发病趋势分析

Study on the epidemiological characteristics and incidence trend of scarlet fever in Shanghai, 2005-2012

Received:March 01, 2013

DOI：10.3760/cma.j.issn.0254-6450.2013.07.010

KeyWord: 猩红热 A组链球菌发病特征组合模型

English Key Word: Scarlet fever Group A Streptococcus Epidemic characteristics Combined mathematical model

FundProject:上海市公共卫生重点学科建设计划(12GWZX0101)

Author Name	Affiliation	E-mail
REN Hong	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
WANG Ye	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
CHEN Ming-liang	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
YUAN Zheng-an	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
LI Yan-ting	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
HUANG Pu	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China
HU Jia-yu	Shanghai Municipal Center Disease Control and Prevention, Shanghai 200336, China	jyhu@scdc.sh.cn

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Abstract:

目的系统分析2005-2012年上海市猩红热发病特征及健康人群A组链球菌(GAS)携带状况, 探讨健康人群GAS监测和组合模型预测技术在猩红热早期预警中的应用。方法使用国家法定传染病报告数据分析上海市猩红热的流行特征。构建自回归移动平均模型(ARIMA)和人工神经网络(ANN)组合模型, 对猩红热月度报告发病率进行分析和预测。采用GAS分离培养、菌型鉴定试验、emm分型和超抗原基因检测技术, 监测猩红热流行期间健康人群GAS携带状况, 并计算GAS标准化带菌率。结果2005--2012年上海市共报告猩红热病例9410例, 以散发为主, 发病呈现季节性和周期性。2011年报告发病率达到高峰, 年均报告发病率6.012/10万, 患者以4。8岁年龄段托幼儿童和学生为主, 郊区人群发病率显著高于市区, 发病的性别差异无统计学意义。单纯ARIMA模型、ARIMA-GRNN组合模型和ARIMA.BPNN组合模型的平均相对误差(MER)分别为0.268、0.432和0.131。使用预测效果最优的ARIMA．BPNN组合模型进行预测, 2013年l-6月上海市猩红热月度发病率将波动在o.446/10万至3.467/10万。2008年和2010年上海市<15岁社区健康人群未发现GAS带菌者, 而2012年带菌率为1.180%, 标准化带菌率为1.092%。2012年分离获得18株GAS, 其中15株为emm 12.0型(83.33%)。结论上海市猩红热报告发病率将继续小幅上升。社区健康人群GAS带菌率监测和组合模型预测技术可用于猩红热的早期预警。

English Abstract:

ObjectiveTo systemically analyze the epidemiological characteristics, molecular markers of circulating group A Streptococcus(GAS)isolates and the incidence trend of scarlet fever in Shanghai from 2005 to 2012 as well as to explore the practice of GAS isolates surveillance program and the combined mathematical model in the early warning of scarlet fever.MethodsThe morbidity series of scarlet fever were retrieved to analyze and fit the combined mathematical model which comprised an autoregressive integrated moving average(ARIMA)model and a neural network.GAS isolates surveillances programs were implemented on community healthy population, using the emm typing and superantigens detecting method in Shanghai during the epidemic period of scarlet fever in 2008, 2010 and 2012．The standardized prevalence of GAS isolares was estimated with the demographic data.ResultsFrom 2005 to 2012.there were a total of 9410 scarlet fever cases reported in Shanghai including local registered residents and immigrant population, showing that the distribution of patients as sporadic．The morbidity kept rising with seasonal and periodical variations and the peak was in 2011.The average morbidity was 6.0l2 per l00000 persons．Morbidity in the the suburban was significantly higher than that in the urban areas．Children at 4 to 8 years old were easy to be involved.The mean error rate of single ARIMA model．ARIMA．GRNN and back propagation artificial neural network combined model were 0.268.0.432 and 0.13l respectively.The predicted incidence of scarlet fever in 2013 would keep fluctuating within a narrow range from 0.446 to 3.467 per l00000 persons.A total number of 4409 throat swab samples were collected through the GAS isolates surveillance programs in 2008．2010 and 2012.The standardized prevalence of GAS isolates in each year were 0.000%.0.000%and 1.092%.18GAS isolates were identified and 15 isolates(83.33%)belonged to emm 12.0.ConclusionThe morbidity of scarlet fever would continue to maintain an upward trend in Shanghai and the techniques used in GAS isolates surveillance program and in the combined mathematical model could be applied for the early warning system on scarlet fever．

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