| Objective:To explore and analyze the spatio-temporal characteristics of influenza in Jiangxi Province,as in order to detect the spatio-temporal gathering points and identify the potential gathering risks,besides clarify the spatio-temporal clustering pattern and evolution rule of influenza,finally systematically grasp the real clustering risk and evolution trend of the incidence of influenza in our province,and visually display the clustering areas and risk pattern,that will provide scientific basis for early warning and prevention and control of influenza cluster risk,and also to lay the research foundation for carrying out the spatio-temporal regularity and early risk warning of other key infectious diseases more systematically and deeply in the future.Methods:By formulating a unified case surveillance and investigation program,also in accordance with the standard of the case definition and cluster epidemic,surveillance and sampling of influenza-like cases clustering in 11 cities of Jiangxi Province were carried out,and influenza monitoring was carried out by the township health centers and other medical institutions above the township level,meanwhile the basic information of influenza cases was collected and reported in the monitoring information system.In addition,statistical methods such as spatio-temporal scanning statistics,spatial autocorrelation and spatio-temporal hot spots analysis were used to analyze the incidence distribution,finally spatio-temporal clustering points and clustering patterns were visualized by map..Result:(1)From 2017 to 2019,there was an epidemic peak in winter and spring every year in Jiangxi Province,with the highest incidence in Ganzhou,and the annual incidence was more than twice of the provincial average.The incidence is mainly concentrated in people under 15 years old,accounting for about 50%;The cluster of influenza-like cases mainly occurred in primary and middle schools,accounting for72.90% and 17.42% of the total,respectively.Xinyu,Nanchang,Ganzhou and Fuzhou reported more clusters of outbreaks,accounting for 37.42%,21.94%,15.48% and10.97% of the total,respectively.(2)Retrospective spatiotemporal scanning analysis detected four types of spatiotemporal aggregation regions at both the prefectural and county levels.The first type agglomeration area were 16 counties and districts in southern Jiangxi Province on December 19,2018 solstice on April 25,2019(RR=9.72,LLR=15061.27,P <0.01);The second type clustering area were the 13 counties in the north of Jiangxi Province(RR=20.68,LLR=3867.86,P<0.01);The three types of clustering areas were 18 counties and districts in the northeast of Jiangxi Province(RR=3.13,LLR=1297.439,P<0.01);The four clustering regions were 17 counties and districts in western Jiangxi on December 2,2019(RR=5.09,LLR=1233.47,P<0.01).(3)Prefecture-level global autocorrelation analysis showed a random distribution of annual influenza incidence;The results of county level analysis showed that there were spatial clustering and positive correlation(Z=2.58,P<0.01);Local autocorrelation analysis at the prefecture-level showed that there were two clustering regions in the whole province in 2017,among which Ganzhou City wa s high-low clustering(Z=-2.03,P <0.05),low-low concentration in Yichun(Z=-2.17,P<0.05);In2018,there was one high-low aggregation region,which was Ganzhou City(Z=-2.43,P<0.05);In 2019,there was a high-low aggregation region in Ganzhou City(Z=-2.55,P<0.05);Local autocorrelation analysis at the county and district level showed that there were 6 clustering regions in 2017,including 4 high-high clustering regions,1high-low clustering region,and 1 low-high clustering region.Huichang County,Anyuan County,Xinwu County and Dayu County were high-high clustering regions(Z>1.96,P<0.05);In 2018,there were 8 clustering regions in all counties and districts of the province,all of which were high clustering regions,including Dayu County,Chongyi County,Anyuan County,Longnan County,Dingnan County,Huichang County,Xinwu County and Ruijin City(Z>1.96,P<0.05);In 2019,there were 6clustering regions in all counties and districts of the province,all of which were high clustering regions,including Anyuan County,Longnan County,Dingnan County,Huichang County,Shicheng County and Ruijin City(Z>2.58,P<0.05).(4)Spatiotemporal hot spot analysis of prefecture-level influenza incidence showed that in 2017(ZGizscore =-2.75,P<0.01)and 2018(ZGiz Score =-2.32,P <0.01)there was one cold spot in each area,all of which were in Yichun City,but no hot spot was detected.County-level analysis showed that there were 9 hot spots and 1 cold spot in each county and district in 2017.All 9 hot spots were located in Ganzhou City,and the cold spot was located in Yichun City.In 2018,there were 10 hot spots,all of which were in Ganzhou City;In 2019,there were 13 hot spots,12 hot spots were in Ganzhou City,and 1 hot spot was in Fuzhou City.ZGizscore was statistically tested,and all of the P values were lower than 0.05.Conclusion:(1)There are obvious seasonal,regional and population high incidence of influenza in Jiangxi Province,and there are clustered epidemics in local areas every year.The epidemic prevention and control of Ganzhou City,people under 15 years old and primary and secondary schools are the key points for the annual epidemic prevention and control of influenza in Jiangxi Province.The prevention and control of influenza in winter and spring will play a decisive role in reducing the overall incidence level of influenza in Jiangxi Province.(2)From 2017 to 2019,influenza in Jiangxi Province showed spatio-temporal aggregation at both city and county scales.Four types of spatio-temporal aggregation regions were detected at both scales.The spatio-temporal distribution of aggregation sites at city and county levels were consistent,but the aggregation periods were different in different regions,and the aggregation periods were mainly in late winter and spring.(3)There was a significant spatial autocorrelation and clustering of influenza in Jiangxi Province during2017-2019.The spatial clustering at the municipal level is relatively simple,while the spatial clustering at the county level is obvious.The high clustering is mainly found in the counties under the jurisdiction of Ganzhou City,so it is more reliable and accurate to detect the spatial clustering at the county level.(4)There were obvious spatiotemporal hot spots in the incidence of influenza in Jiangxi Province from 2017 to 2019.Municipal only detect cold spot area in 2017 and 2018,but every year there are hot spots of time and space at county scale,mainly concentrated in ganzhou city,and the hot spots in expanding,county scale hot spots of time and space and space gathering area is consistent,high incidence in space and time to gather for county scale mining features finer more appropriate. |
PDF Full Text Request