Application of the rapid influenza testing during 2007-2008 flu season in Beijing city / 中华检验医学杂志

Objective To analyze the application value of the rapid testing for influenza during 2007-2008 flu season at fever clinic in Beijing Chaoyang hospital Methods 500 patients with diagnosis of influenza-like illness were prospectively enrolled. Pharyngeal swabs were collected for influenza viral culture and rapid testing for influenza. Demographic characteristics, age, symptoms, lab tests, symptom recovery time and medical expense were also collected. The sensitivity, specificity, positive predictive value and negative predictive value for rapid testing were analyzed. Results A total of 500 patients were enrolled between Dec 2007 and March 2008. Among them 498 cases were used for analysis. Influenza B was most common by virus culture methed(n=208,41.8%) ,followed by influenza A (n=51,10.2%). The average age was 35, and the ratio of male to female was 1.47:1. Compared with the group of positive culture, patients with influenza were more likely to get cough, sore throat, and nasal congestion (t=13.728, 4.014and 4.720,P<0.001 or 0.05, respectively). A total of 260 cases were subjected to rapid testing, Among them 18 cases were influenza A positive and 132 cases were influenza B positive. The rapid testing had a sensitivity of 77.1 % and a specificity of 70.1%. The positive predictive value was 78.6% and the negative predictive value was 68.2%. The rapid testing had enhanced the proportion of anti-viral treatment from 0 to 26% and reduced the proportion of antibiotic use from 63.4% to 20. 7%. Conclusions Influenza B is the most predominant pathogen during 2007-2008 flu season among patients with influenza-like illness in Beijing. The rapid testing with high sensitivity and specificity provides guidance on clinical practice.

The Application of the Prediction of the Reported Weekly Incidence of Bacillary Dysentery in Chaoyang District Using the Time Series Model / 中国卫生统计

Objective The study estabfished a model to pre-dict the weekly incidence of bacillary dysentery in Chaoyang District,and evaluated its predictive effects. Methods To eliminate the factors of sea-son-changing by means of Time Series. Auto regressive integrated moving average(ARIMA), based on model identification, estimation andverifica-tion of parameter, and analysis of the fitting of model, was established. Fi-nally,the predictive model was established by the multiple of ARLMA and seasonal factors. Results The error of the model for the prediction was -0.06 on average. The relative error was 2.32% on average. Conclusion Time series could not only accurately predict useing the data which was collected every week,but shorten the cycle of prediction.