摘要
目的 分析通辽市不同年份成蚊密度,通过拟合求和自回归移动平均模型(autoregressive integrated moving average, ARIMA)对未来蚊虫密度进行预测。方法 选用诱蚊灯法监测通辽市2017—2021年不同生境成蚊密度,根据监测结果,建立ARIMA模型,对2022年成蚊密度进行预测。结果 2017—2021年通辽市各监测点平均蚊密度为7.91只/(灯·夜)。其中淡色库蚊为优势蚊种。在五类生境中,除2017年农户蚊密度较高外,其他年份都是牲畜棚密度较高。每年成蚊密度均为单峰曲线,除2017年高峰出现在7月份外,其余年份高峰均出现在8月,根据2017—2021年蚊虫密度结果,拟合ARIMA(1,1,1)×(1,1,0)_(12)模型,残差序列为白噪声序列(Q=14.498,P=0.488),用此模型预测2022年的成蚊密度,5—10月份分别为8.12、7.48、13.79、29.31、22.08和12.37只/(灯·夜)。结论 利用2017—2021年的数据建立ARIMA模型,能够预测2022年的成蚊密度和季节消长趋势,为进一步蚊媒传染病风险评估提供理论数据支持。
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.
作者
邵华
布仁巴图
秦忠良
商娜
倪晓娜
张志平
李莹盈
SHAO Hua;BUREN Ba-tu;QIN Zhong-liang;SHANG Na;NI Xiao-na;ZHANG Zhi-ping;LI Ying-ying(Tongliao Municipal Center for Disease Control and Prevention,Tongliao,Inner Mongolia 028000,China)
出处
《实用预防医学》
CAS
2023年第2期242-245,共4页
Practical Preventive Medicine
基金
内蒙古自治区科技计划项目(2021GG0312)
关键词
蚊密度
预测
求和自回归移动平均模型
mosquito density
forecast
autoregressive integrated moving average model
