| 孟蕾,王新华,李娟生,任晓卫,李红育,胡晓斌,杨筱婷,秦林原,陈建华,白亚娜.甘肃省2006-2011年哨点监测流感样病例动态预警分析[J].Chinese journal of Epidemiology,2012,33(11):1155-1158 |
| 甘肃省2006-2011年哨点监测流感样病例动态预警分析 |
| Dynamic prediction on the number of influenza-like cases in Gansu province based on data from the influenza sentinel surveillance program, from 2006 to 2011 |
| Received:July 10, 2012 |
| DOI：10.3760/cma.j.issn.0254-6450.2012.11.013 |
| KeyWord: 流感 预警 哨点监测 |
| English Key Word: Influenza Early warning Sentinel surveillance |
| FundProject:国家科技重大专项(2009ZXl0004—208) |
| Author Name | Affiliation | E-mail | | MENG Lei | Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China | | | WANG Xin-hua | Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China | | | LI Juan-sheng | School of Public Health, Lanzhou University | | | REN Xiao-wei | School of Public Health, Lanzhou University | | | LI Hong-yu | Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China | | | HU Xiao-bin | School of Public Health, Lanzhou University | | | YANG Xiao-ting | Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China | | | QIN Lin-yuan | School of Public Health, Lanzhou University | | | CHEN Jian-hua | Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China | | | BAI Ya-na | School of Public Health, Lanzhou University | baiyana@lzu.edu.Cn |
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| Abstract: |
| 目的 掌握甘肃省流感样病例发生动态并探索其预警模式和效果.方法 通过甘肃省2006-2011年哨点流感样病例监测数据，应用时序图分析其变动趋势，并采用流行控制图-移动百分位数法探索流感样病例预警模式，结合统计模型的预测值，评价预警效果.结果 甘肃省2006和2009年为流感高流行期，2007和2008年为流感低流行期.流感样病例流行控制预警线显示冬季预警值较高，夏季较低的特征.应用简单季节性指数平滑模型和自回归移动平均模型(ARIMA)(1，1，1)(0，1，0)乘积季节性模型动态预测2011年每周流感样病例占门急诊病例百分比(ILI％)，二者动态预测预警与实报预警一致率均为100％.但从预测的均方根误差分析，指数平滑模型动态预测效果优于ARIMA模型.结论 流感动态预警模式可反映甘肃省流感样病例的流行规律，但预警技术存在局限性. |
| English Abstract: |
| Objective To understand the epidemiological trend on the number of influenzalike cases and to explore the feasibility of early warning systems of influenza in Gansu province. Methods Based on data from the influenza sentinel surveillance program, a sequence chart was used to analyze the epidemiological trend on the number of influenza-like illness (ILI) cases. Both control chart and mobile percentile method were used to select the threshold of premium alert for the ILI of sentinel surveillance program. Warning effects were assessed by statistical model. Results The prevalence of influenza were both low in 2007 and 2008. Alert thresholds for ILI of Sentinel surveillance was built. The thresholds were higher alert in winter, but lower in summer. Both Seasonal Exponential Smoothing Model and Multiplicative Seasonal ARMA Model (1, 1, 1) (0, 1, 0) were used to dynamically predict the weekly percentage of outpatient visits for influenza-like illness (ILI％)of 2011. The concordance rates (predicted=actual) were 100％ for both of them. According to the RMSE values, the dynamically predicted effect of the seasonal exponential smoothing model was superior to ARIMA. Conclusion Dynamic prediction on the number of influenza-like cases could reflect the epidemiological trend of influenza in Gansu province, but with some limitations. |
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