Abstract: Objective To predict the density of Aedes albopictus in Songjiang district, Shanghai, China, using a seasonal trend model based on moving average method, and to provide a justification for mosquito control and dengue fever warning. Methods Using Microsoft Excel 2003, an equation was fitted to the monthly time series data of mosquito ovitrap index (MOI) of Ae. albopictus in Songjiang district, Shanghai, from 2014 to 2018 to establish a prediction model, and the model was used to predict the density trend of Ae. albopictus in 2019. Results The seasonal trend model based on moving average method had a relatively good fit with an average relative error of 12.82%; therefore, it could predict the changing trend and seasonal characteristics of Ae. albopictus density. In 2019, the density of Ae. albopictus in Songjiang district would generally be still high, with a single peak density in July; the MOI would be less than 5 in April, more than 5 from May to November and more than 10 from June to September. Conclusion By closely surveillance on the density of Ae. albopictus and taking account of the prediction results of the seasonal trend model, an early warning can be issued and mosquito prevention and control measures can be taken in time to reduce the risk of dengue fever epidemics.

Key words: Aedes albopictus, Moving average method, Seasonal trend model, Prediction

摘要： 目的 应用移动平均法的季节趋势模型预测上海市松江区白纹伊蚊密度，为蚊虫防制和登革热预警提供依据。方法 利用Excel 2003对上海市松江区2014－2018年白纹伊蚊诱蚊诱卵器指数（MOI）以月为时间序列拟合方程建立预测模型，并对2019年白纹伊蚊密度趋势进行预测。结果 移动平均法季节趋势模型拟合的平均相对误差为12.82%，模型拟合较好，可预测白纹伊蚊密度变化趋势和季节特征；2019年松江区白纹伊蚊密度整体上仍较高，单峰分布，密度高峰在7月，仅4月MOI<5，5－11月的MOI均>5，6－9月的MOI均>10。结论 密切监测白纹伊蚊密度，结合季节趋势模型的预测结果，提前做出预警，及时采取蚊虫控制措施，降低登革热流行风险。

关键词: 白纹伊蚊, 移动平均法, 季节趋势模型, 预测