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.
LYU Xi-hong, WANG Rui-ping, GUO Xiao-qin, FEI Sheng-jun, PANG Bo-wen, LENG Pei-en
. Predicting the density of Aedes albopictus in Songjiang district, Shanghai, China, using a seasonal trend model[J]. Chinese Journal of Vector Biology and Control, 2019
, 30(4)
: 427
-429
.
DOI: 10.11853/j.issn.1003.8280.2019.04.016
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