An 8-year cohort study on mosquito population dynamics and meteorological factors in a eastern coastal area of China

This study aims to elucidate the dynamic patterns of mosquito species composition and density across seasons and habitats in Yandu District, Yancheng City, from 2016 to 2023 and quantitatively assess the impact of key meteorological factors on population variations, thereby providing a basis for precise risk forecasting of mosquito-borne diseases. Mosquito surveillance was conducted monthly from 2016 to 2023 across 13 sampling sites in urban, rural, and wetland areas of Jiangsu Province using light traps (12 trap-hours per session). Daily meteorological data, including temperature, rainfall, and wind speed, were obtained from local weather stations. Statistical analyses were performed using SAS 9.1 and GraphPad Prism 10. Spearman’s correlation and the Mann-Kendall test were applied to assess relationships and trends. A Generalized Additive Model via Penalized Likelihood (GAMPL) was employed to capture nonlinear effects of meteorological factors on mosquito density, while a Generalized Linear Model (GENMOD) was used to evaluate linear associations. All analyses used a significance level of α = 0.05. From 2016 to 2023, a total of 103,901 mosquitoes were captured via light trapping, with an overall density of 15.04 individuals/(lamp·h). These mosquitoes belonged to 8 species, 4 genera, and 2 subfamilies. The dominant species were Culex pipiens pallens (65.66%), Culex tritaeniorhunchus (18.90%), and Anopheles sinensis (10.29%), accounting for 94.85% of the total captures. Monthly mosquito density showed a unimodal distribution, peaking at 29.11 individuals/(lamp·h) in July. Spatially, the annual average mosquito density in wetland parks (45.78 individuals/(lamp·h)) was significantly higher than that in urban environments ( P < .01 ). Spearman correlation analysis revealed significant correlations between mosquito density and mean temperature, maximum temperature, minimum temperature, and mean precipitation (PRCP) (all P < .001 ). Generalized linear regression indicated that when temperature exceeded 20°C, each 1°Cincrease was associated with an absolute increase of 1.64 individuals/(lamp·h) in mosquito density ( β = 1.64 ). GAMPL analysis demonstrated a significant nonlinear effect of PRCP on mosquito density, with a smoothed component plot showing an inverted “U” shape. Based on these observational findings, mosquito management strategies may benefit from prioritizing wetland and rural zones during July. Furthermore, temperature-precipitation data could potentially inform early warning systems to guide localized control efforts.