桂林市禽流感外环境监测数据的时空特征分析

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

目的了解桂林市禽流感外环境病毒污染情况,为禽流感疫情防控和预警提供参考数据。方法收集、汇总桂林市2010—2020年禽流感外环境监测数据,对不同年份、不同季节的外环境病毒阳性样本数进行趋势卡方检验;结合环境数据,对阳性检出数与人口密度进行线性相关分析和非线性相关分析;应用方向分布、趋势、空间自相关、高/低聚类(General G)和热点分析等方法分析空间分布。结果2010—2020年桂林市禽流感外环境病毒阳性检出数552例,阳性率为35.5%。阳性检出率秋冬季较高,中部比周边高,且与人口密度呈线性正相关;空间方向分布不明显,大致呈现“东北-西南”的分布模式;阳性标本分布存在高值聚集趋势,以叠彩区、七星区、秀峰区、象山区为“热点区域”。结论2010—2020年桂林市禽流感外环境病毒阳性检出情况在时间上与季节有关,空间上呈中部聚集趋势,且与人口密度呈线性正相关。

Objective To understand the virus pollution situation in the external environment of avian influenza in Guilin,and to provide data reference for the prevention,control,and early warning of avian influenza epidemic.Methods The external environmental monitoring data of avian influenza in Guilin from 2010 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 different time and season,linear and nonlinear correlation analysis were conducted between positive detection numbers and population density based on environmental data.Methods such as directional distribution,trend,spatial autocorrelation,high/low clustering,and hotspot analysis for spatial distribution analysis.Results From 2010 to 2020,there were 552 positive cases of avian influenza virus in the external environment of Guilin,with a positive rate of 35.5%.The positive detection rate is higher in autumn and winter.There are more cases in the central area than in the surrounding areas with a positive linear correlation with population density.The spatial distribution is not obvious,showing a slightly"northeast southwest"distribution pattern.The distribution of positive specimens shows a trend of high value aggregation,with Diecai District,Seven Star District,Xiufeng District,and Xiangshan District being the"hot spots".Conclusion The positive detection of avian influenza virus in the external environment of Guilin from 2010 to 2020 is related to season in time,shows a central clustering trend in space,and has a linear positive correlation with population density.