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
10.3760/cma.j.issn.0254-6450.2012.11.013
- VernacularTitle:甘肃省2006-2011年哨点监测流感样病例动态预警分析
- Author:
Lei MENG
1
;
Xin-Hua WANG
;
Juan-Sheng LI
;
Xiao-Wei REN
;
Hong-Yu LI
;
Xiao-Bin HU
;
Xiao-Ting YANG
;
Lin-Yuan QIN
;
Jian-Hua CHEN
;
Ya-Na BAI
Author Information
1. 甘肃省疾病预防控制中心
- Keywords:
Influenza;
Early warning;
Sentinel surveillance
- From:
Chinese Journal of Epidemiology
2012;33(11):1155-1158
- CountryChina
- Language:Chinese
-
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.
