Objective To investigate the relationship between mosquito density fluctuations and meteorological factors, so as to provide a scientific basis for mosquito surveillance analysis, risk assessment, and comprehensive prevention and control.

Methods Mosquito surveillance and monitoring data of 2020‒2023 was obtained from on-site supervisory sampling by Songjiang Center for Disease Control and Prevention, and meteorological data was obtained from the Wheat A wheat malt-agro-meteorological big data system. Excel 2019 and SPSS 25.0 software were used to organize and analyze the mosquito number, species composition, and seasonal changes in mosquito density captured by the CO₂-light trap at rach monitoring site. Circular distribution method was used to calculate the peak time of mosquito density, combined with the meteorological data of the same period to explore the impact of meteorological factors on the results of mosquito surveillance.

Results There was a statistical difference in the overall distribution of mosquito quantity in different habitats(H=23.11, P<0.05), 2020‒2023. In addition, the results showed that July 28th was the peak day for mosquito density, and the duration from June 13th to September 11th was the seasonal peak period for mosquitoes. Pearson correlation analysis showed a positive correlation between mosquito density and average air temperature, average highest air temperature, average lowest air temperature, extreme maximum air temperature, extreme minimum air temperature, precipitation, and number of precipitation days (all P<0.01). While, there was no significant correlation between average wind speed and mosquito density (P>0.05). Multiple stepwise regression analysis resulted in the equation of Y=0.151X_{extreme minimum temperature}+0.321X_{number ofprecipitation days}+1.002X_{SQRT precipitation}-1.288 (F=102.635, P<0.05).

Conclusion The CO₂-light trap is advisable to monitor the habitats of farmers, livestock sheds, residential areas, parks, hospitals, and other external environments. Air temperature and precipitation have a significant impact on mosquito density. It is recommended to implement comprehensive prevention and control measures to reduce mosquito density and prevent mosquito-borne diseases before the peak period of mosquitoes.