关键词: 病媒生物, 密度, 空间插值, 空间自相关

Abstract: Objective To investigate the spatial distribution characteristics and spatial aggregation at subdistrict scale of vector density during peak period in the main urban area of Hefei, Anhui Province, China, so as to provide a reference for optimization of vector control measures and prevention and control of vector-borne infectious diseases. Methods The surveillance data of vector density during the peak period in 2024 were collected for the main urban area of Hefei. The data were plotted in thematic maps. Ordinary Kriging interpolation and spatial autocorrelation were used to analyze the spatial distribution characteristics of vector density. Results The average densities of rodents, mosquitoes, flies, and cockroaches in the main urban area of Hefei were 0.91%, 3.50 mosquitoes/lamp·night, 4.54 flies/cage, and 0.05 cockroaches/trapping paper, respectively. The coefficients of determination (R²) for the interpolated densities of rodents, mosquitoes, flies, and cockroaches were 0.78, 0.86, 0.71, and 0.66, respectively. The corresponding root mean square errors were 0.24, 0.28, 0.28, and 0.53, respectively. The densities obtained by ordinary Kriging interpolation were 0.03%-3.22%, 0.04-13.80 mosquitoes/lamp·night, 0.33-11.05 flies/cage, and 0.00-0.14 cockroaches/trapping paper. The ranges of interpolated densities were narrower than those of the actual surveillance values, but the distributions were generally consistent. The spatial distributions of densities of rodents, mosquitoes, flies, and cockroaches showed positive correlations, with Moran's I indexes of 0.51, 0.35, 0.21, and 0.42, respectively (all Z>0, P<0.01). The 16 subdistricts covered by the "high-high" aggregation areas of vector density were mainly distributed in the northeastern region, and the 24 subdistricts covered by the "low-low" aggregation areas formed a contiguous zone spanning the northern, central, and southeastern regions. Conclusions Vector density during peak period was relatively low in the main urban area of Hefei. The densities of different vectors showed uneven spatial distributions, and an overall spatial pattern of high in the east and north and low in the west and south. Spatial aggregation was observed at the subdistricts scale. Sustainable and differentiated control measures should be developed, with a focus on key areas at risk for vector-borne diseases.

Key words: Vector, Density, Spatial interpolation, Spatial autocorrelation