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自回归滑动平均混合(autoregressive integrated moving average,ARIMA)模型在部分传染病中的应用研究结果表明,其拟合效果好,预测效果可靠,能较好地辅助传染病的预防与控制[1-5]。流行性感冒(简称流感)是严重威胁人类生命的急性呼吸道传染病之一,其流行具有周期性。对流感监测并开展有效的预测分析对于认识流感流行规律和预防流感流行起着至关重要的作用。甘肃省自2006年以来开始实施较为系统的流感症状监测,形成了较稳定的流感监测网络。本研究利用甘肃省2006—
The application of autoregressive integrated moving average (ARIMA) model in some infectious diseases shows that the fitting effect is good and the prediction effect is reliable, which can better assist the prevention and control of infectious diseases [1-5 ]. Influenza (influenza) is one of the acute respiratory diseases that threaten human life, and its epidemic is cyclical. Monitoring influenza and developing effective predictive analytics are critical to understanding the epidemic and preventing influenza. Since 2006, Gansu Province has started systematic monitoring of flu symptoms and has formed a relatively stable influenza surveillance network. This study uses Gansu Province in 2006-