Objective To investigate the density of rodents at the national surveillance sites (Ji'nan, Qingdao, and Liaocheng) in Shandong province of China and to discuss the application of autoregressive integrated moving average (ARIMA) model in rodent density prediction and warning. Methods The night trap/cage method was used to monitor the density of rodents, and R 3.6.2 software was used to establish the ARIMA model for rodent density data in each monitoring month from 2010 to 2018. The predicted rodent density was compared with the actual rodent density in each monitoring month in 2019 to evaluate the prediction effect of the model. Results The average rodent density was 0.80% at the national surveillance sites in Shandong province in 2010-2018. The ARIMA model was used for the fitting of rodent density at the national surveillance sites in Shandong province in 2010-2018. With ARIMA (0,1,1)×(0,1,1)6 as the optimal model and white noise sequence as the residual sequence (χ2=0.035, P=0.832), this model was used to predict rodent density in each monitoring month of 2019, and the actual monitoring values fell within the 95% confidence interval of the predicted values. The seasonal variation trend of rodent density was basically consistent with the observed value, suggesting that the model could be used to predict rodent density in the short and medium term. Conclusion The ARIMA (0,1,1)×(0,1,1)6 model is well fitted with rodent density at the national surveillance sites in Shandong province and can be used for the prediction and early warning of rodent density, so as to provide a basis for the prevention and control of rodent-borne diseases.
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