【摘要】目的 基于南京地区蚊虫侵害密度，建立季节性差分自回归移动平均模型预测方法，为进一步防控蚊媒病和开展爱国卫生运动提供新的思路和方法。方法 应用季节性差分自回归移动平均模型对2019年蚊虫密度进行预测。结果 拟合后的预测模型为：ARIMA（2,1,0）（1,1,0）12，模型残差序列为白噪声，模型预测拟合后R2=0.9067。 结论 模型预测的拟合效果较好，说明ARIMA模型适用于开展蚊虫侵害预测研究。
【Abstract】Objective Based on the mosquito infestation density in Nanjing, a seasonal differential autoregressive moving average model prediction method was established to provide new ideas and methods for the further prevention and control of mosquito-borne diseases and the development of patriotic health campaigns. Methods The seasonal difference autoregressive moving average model was used to predict the mosquito density in 2019. Results The fitted prediction model was: ARIMA(2,1,0)(1,1,0)12, the model residual sequence was white noise, and the model prediction was fitted with R2=0.9067. Conclusion The fitting effect of the model prediction is good, indicating that the ARIMA model is suitable for the study of mosquito infestation prediction.