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Analysis of spatial-temporal characteristics of avian influenza externalenvironment monitoring data in Guilin

【来源:《华夏医学》编辑部 | 作者:WANG Linyan,etc. | 编辑:李佳睿 | 发布日期:2024-09-19】

WANG Linyan1,PAN Xiaowen2, ZENG Xi1, TAN Chao1

(1. College of Publie Health, Guilin Medical University, Guilin 541199, China; 2. Guilin Center for DiseaseControl and Prevention,Guilin 541000.China)

AbstractObjective To understand the virus pollution situation in the external environment of avianinfluenza in Guilin, and to provide data reference for the prevention , control, and early warning of avianinfluenza epidemic. Methods The external environmental monitoring data of avian influenza in Guilin from2010 to 2020 were collected and analyzed. Chi square test and trend test were performed on the number of

positive samples of virus in the external environment at diflerent time and season, linear and nonlinear correlation analysis were conducted between positive deteetion numbers and population density based onenvironmental data. Methods such as directional distribution, trend, spatial autocorrelation, high/lowclustering, and hotspot analysis for spatial distribution analysis. Results From 2010 to 2020, there were552 positive cases of avian inlluenza virus in the external environment of Guilin, with a positive rate ol35.5 %. The positive detection rate is higher in autumn and winter. There are more cases in the central areathan in the surrounding areas with a positive linear correlation with population density. The spatialdistribution is not obvious , showing a slightly " northeast southwest" distribution pattern. The distribution ofpositive specimens shows a trend of high value aggregation, with Diecai District, Seven Star District.Xiufeng District , and Xiangshan Distriet being the " hot spots". Conclusion "The positive detection of avianinfluenza virus in the extemal environment of Guilin from 2010 to 2020 is related to season in time. showsa central clustering trend in space , and has a linear positive correlation with population densityKeywords : avian influenza; spatiotemporal analysis ; geographic information system ; exteral environmentalmonitoring

DOI:10.19296/j.cnki.1008-2409.2024-01-011

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