流感样疾病对门诊人数的影响

Effect of influenza-like diseases on the number of outpatient visits

目的用流感样病例数(ILI)预测门诊就诊人数,以估计流感对人群健康的影响。方法资料来源于广州市两所流感监测医院的内科、儿科和急诊科的每周门诊人数和ILI病例数,时间从2002年第22周至2004年第53周,共137周。应用谱分析和时间序列方法分析门诊人数的变化趋势。以ILI为自变量,门诊人数为因变量,建立预测模型,最优模型的选择依据于决定系数、池田信息准则(AIC)、残差分析及对模型的前瞻性考核。结果两年的门诊人数呈线性上升(P<0.001),并具备一定的周期性。门诊人数与ILI之间呈显著正相关(r=0.568,P<0.001)。自回归模型的残差为白噪声序列,模型的决定系数为0.75,前瞻性考核发现模型的决定系数为0.56。结论可用自回归模型分析ILI与门诊人数的关系,进而用于评估流感对人群健康的影响。

Objective To estimate the effect of influenza-like illness （ILI） on outpatient visits and assess its impact on public health. Methods We analyzed the data of weekly number of ILI and outpatient visits in Departments of Internal Medicine, Pediatrics and Emergency at two influenza surveillance hospitals during a period of 137 weeks in Guangzhou. Spectral analysis and time-series analysis were performed to evaluate the variation of outpatient visits over time. The predictive model was fitted with weekly outpatient visits as the dependent variable and weekly number of ILI as the independent variable. The optimal model was established according to the coefficient of determination, Akaikeinformation criterion and residual analysis. The validity of the model was assessed prospectively using the 31-week data that were not used for the model establishment. Results The outpatient visits increased significantly over time and showed significant seasonality （P〈0.001）. A significant correlation was found between the weekly number of ILI and outpatient visits （r=0.568, P〈0.001）. The residuals of the fitted autoregression model were white-noise series and the coefficient of determination was 75% for the data used to establish the model and 56% for the subsequent 31-week data. Conclusion The autoregression model can be used to estimate the effect of weekly number of outpatient visits based on the weekly number of ILI and thus assess the effects of influenza on public health.