自回归积分移动平均模型在长沙市白纹伊蚊密度预测中的应用

Application of autoregressive integrated moving average model in predicting the density of Aedes albopictus in Changsha City

目的探讨自回归积分移动平均(autoregressive integrated moving average,ARIMA)模型在长沙市三种方法监测白纹伊蚊密度预测中的应用,预测密度增长趋势。方法收集整理长沙市2007年1月—2023年7月诱蚊灯法及2016年1月—2023年7月双层叠帐法、布雷图指数法监测白纹伊蚊密度数据,采用2007年1月—2022年12月诱蚊灯法监测数据、2016年1月—2022年12月双层叠帐法及布雷图指数法监测数据,应用R4.3.0软件分别构建季节性ARIMA模型,将2023年1—7月的三种方法监测数据实际值与预测值进行比较评价,预测2023年8—11月密度。结果对三种方法监测白纹伊蚊密度分别构建了最佳模型ARIMA(0,0,1)(2,1,2)12、ARIMA(0,1,1)(0,1,1)12及ARIMA(0,1,0)(1,0,2)12,模型赤池信息准则值及贝叶斯信息准则值均达到最低,且较好地拟合了既往密度序列,残差Box-Ljung检验为白噪声(P>0.05),可用于白纹伊蚊密度预测,预测2023年8—11月诱蚊灯法白纹伊蚊密度平均值为0.56只/(灯·夜),预测2023年8—10月帐诱指数及布雷图指数平均值为1.67只/(帐·h)及21.75,均高于2022年同期密度平均值:0.43只/(灯·夜)、0.72只/(帐·h)及3.67。结论ARIMA模型对长沙市三种方法监测白纹伊蚊密度数据构建的最佳模型拟合效果较好,可用于白纹伊蚊密度的短期预测,预测2023年下半年白纹伊蚊密度较2022年同期有增高趋势,应采取措施加大伊蚊密度控制力度。

Objective To explore the application of autoregressive integrated moving average model(ARIMA)in forecasting the density of Aedes albopictus monitored by using three methods in Changsha City so as to predict the growth trend of the density.Methods We collected and sorted out the density data of Aedes albopictus monitored by mosquito trap lamp method(January 2007-July 2023),double layered mosquito net method and Bretto index method(January 2016-July 2023)in Changsha City,and then applied R 4.3.0 to constructing seasonal ARIMA models by using the monitoring data based on mosquito trap lamp method from January 2007 to December 2022 as well as double layered mosquito net method and Bretto index method from January 2016 to December 2022.A comparative evaluation was performed between the monitoring actual data and the predicted values based on the three methods from January to July 2023,and then the density in August-November,2023 was forecasted.Results The optimal models ARIMA(0,0,1)(2,1,2)12,ARIMA(0,1,1)(0,1,1)12 and ARIMA(0,1,0)(1,0,2)12 for monitoring the density of Aedes albopictus were constructed by using the three methods.The Akaike information criterion(AIC)and Bayesian information criterion(BIC)values of the model both reached the lowest levels,and they were well fitted with the previous density sequence.Box-Ljung test showed that the residual sequence was white noise(P>0.05),which could be used for predicting the density of Aedes albopictus.The predictive average value of density of Aedes albopictus based on mosquito trap lamp method from August to November 2023 was 0.56 mosquito/lamp/night,and the predictive average values of the density based on mosquito net trap index and Bretto index from August to October 2023 were 1.67 mosquitoes/net/hour and 21.75 respectively,which were all higher than the average values of the density during the same period in 2022:0.43 mosquito/lamp/night,0.72 mosquito/net/hour and 3.67.Conclusion The optimal ARIMA models have good fitting effects on the density of Aedes albopictus monitored based on the three methods in Changsha City,and can be used for short-term prediction of Aedes albopictus density.The predictive density of Aedes albopictus in the second half of 2023 show an upward trend as compared with that in the same period in 2022.Hence more countermeasures should be taken to control the density of Aedes albopictus.