Abstract：Objective To analyze the mosquito density in Tongliao City in different years, and to predict the future density of mosquito by autoregressive integrated moving average (ARIMA) model. Methods The mosquito trap lamp method was selected to monitor the adult mosquito density in different habitats in Tongliao City from 2017 to 2021. According to the monitoring results, an ARIMA model was established to predict the adult mosquito density in 2022. Results From 2017 to 2021, the average mosquito density at each monitoring site in Tongliao City was 7.91 mosquitoes/(light·night). Among them, Culex pipiens pallens was the dominant mosquito species. Among the five habitats, except for the high mosquito density of peasant household in 2017, the density of livestock sheds in other years was high. The annual adult mosquito density was a single peak curve. Apart from the peak in 2017 occurred in July, the peak in other years occurred in August. ARIMA (1,1,1)×(1,1,0)12 model was fitted according to the results of mosquito density from 2017 to 2021, and the residual sequence was white noise sequence (Q=14.498, P=0.488). This model was used to predict the adult mosquito density in 2022, which were 8.12, 7.48, 13.79, 29.31, 22.08 and 12.37 mosquitoes/(light·night) from May to October, respectively. Conclusion The ARIMA model established based on the data from 2017 to 2021 can predict the density and seasonal fluctuation of adult mosquitoes in 2022 so as to provide theoretical data support for further risk assessment of mosquito-borne infectious diseases.
邵华, 布仁巴图, 秦忠良, 商娜, 倪晓娜, 张志平, 李莹盈. 求和自回归移动平均模型在通辽市成蚊密度预测中的应用[J]. 实用预防医学, 2023, 30(2): 242-244.
SHAO Hua, BUREN Ba-tu, QIN Zhong-liang, SHANG Na, NI Xiao-na, ZHANG Zhi-ping, LI Ying-ying. Application of autoregressive integrated moving average model to the prediction of mosquito density in Tongliao City. , 2023, 30(2): 242-244.
2023, Vol. 30 
