Objective To analyze the population density distributions of adult mosquitoes in different years in Tangshan, Hebei province, China, and to predict future mosquito density by using the autoregressive integrated moving average (ARIMA) model. Methods The lamp trapping method was used to monitor the densities of various adult mosquito populations in different habitats of urban Tangshan from 2010 to 2018. The ARIMA model was established based on the data of the total densities of mosquitoes in each month from 2010 to 2017. Then this model was used to predict the total densities of mosquitoes in every month of 2018, and the prediction effect was evaluated according to the actual densities monitored in 2018. Results During 2010 to 2017, the total density of mosquitoes in urban Tangshan was 2.14 individuals per lamp hour, and Culex pipiens pallens was the dominant species, accounting for 98.02% of the total number of captured mosquitoes. Among different habitats, livestock sheds had the highest mosquito density of 3.65 individuals per lamp hour. There was a significant difference in the composition ratio of mosquito species between different habitats (χ2=249.177, P<0.001). During the eight years, the highest mosquito density (3.00 individuals per lamp hour) was observed in 2014, and the lowest density (1.41 individuals per lamp hour) in 2016. Seasonal fluctuations in the total density of mosquitoes showed a single-peak curve, with the peak at 4.71 individuals per lamp hour in July. An ARIMA model was used to fit the total densities of mosquitoes in urban Tangshan in every month from 2010 to 2017. ARIMA (0, 1, 1)×(2, 1, 0)12 was selected as the best model, and the residual sequence was a white noise sequence (Q=20.654, P=0.148). Then the model was used to predict the total densities of mosquitoes in 2018, and the actual values fell within the 95% confidence interval of the predicted values. The predicted seasonal fluctuations in mosquito density were quite close to the actual values, suggesting this model could be used to predict mosquito density in short and medium term. Conclusion By analyzing the densities of mosquito populations and seasonal fluctuations in Tangshan, the ARIMA model was successfully established to predict future mosquito density, so as to effectively warn the outbreak and epidemic of mosquito-borne diseases.
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