摘要
目的分析2012—2022年河南省开封市猩红热病例的流行病学及空间分布特征,为开封市猩红热的预防控制提供依据。方法对河南省开封市猩红热报告病例进行时间、人群、地区描述性分析,应用ArcGIS 10.6软件绘制猩红热发病统计地图并进行空间自相关分析。结果2012—2022年河南省开封市共报告猩红热病例678例,年均发病率为1.56/10万,发病率呈现先升高后降低的趋势,差异有统计学意义(χ^(2)=859.33,P<0.001)。发病率男女性别差异无统计学意义(χ^(2)=2.01,P>0.05)。病例年龄以<25岁(667例,占98.4%)为主,主要集中于10~<15岁组(374例,占55.2%);10~<15岁组发病率最高,主要为学生(占52.5%),0~13岁发病率呈升高趋势(χ^(2)趋势=6503.22,P<0.001),之后随年龄增加呈下降趋势(χ^(2)趋势=6965.24,P<0.001)。猩红热发病时间呈双峰分布,每年第四季度为发病主峰,发病率为5.55/10万(占32.4%),第二季度为发病次峰,发病率为4.44/10万(26.0%)。开封市西北部中心城区年均发病率(4.56/10万)高于东南部远郊地区(0.39/10万),差异有统计学意义(χ^(2)=864.67,P<0.001)。各区县猩红热发病率空间分布全局空间正相关,存在空间聚集性(Moran’s I=0.129,P=0.02)。局部空间自相关分析显示有5个区县呈现高-高聚集现象。2012—2022年开封市共报告猩红热聚集性疫情33起、暴发疫情9起,主要发生在托幼机构和小学(占83.33%),涉及247例猩红热病例(占36.43%),主要发生在第四季度(占69.05%)和第二季度(占23.81%)。结论2012—2022年河南省开封市猩红热发病率地区分布存在空间聚集特征,主要涉及西北部中心城区且发病率由北向南、由西向东呈下降趋势,建议对重点区域的重点人群有计划开展针对猩红热的预防控制措施。
Objective To analyze the epidemiological and spatial distribution characteristics of scarlet fever cases in Kaifeng City,Henan Province from 2012 to 2022 so as to provide a basis for scarlet fever prevention and control in Kaifeng City.Methods We descriptively analyzed the time,population and region of the reported cases of scarlet fever in Kaifeng City of Henan Province.ArcGIS 10.6 software was used to draw the statistical map of incidence of scarlet fever and perform the spatial autocorrelation analysis.Results A total of 678 cases of scarlet fever were reported in Kaifeng City,Henan Province during 2012-2022,with an average annual incidence rate of 1.56/100,000.The incidence rates showed a trend of first increasing and then decreasing(χ^(2)=859.33,P<0.001).There was no statistically significant difference in the incidence rate between males and females(χ^(2)=2.01,P>0.05).The patients’ages were mainly less than 25 years old(n=667,98.4%),and mainly concentrated at the group aged 10-15 years(n=374,55.2%).The incidence rate was found to be the highest in the group aged 10-15 years,and most of them were students(52.5%).The incidence rates in 0-13 years old showed an upward trend(χ^(2)t rend=6,503.22,P<0.001),but a downward trend with the increase of age(χ^(2)t rend=6,965.24,P<0.001).Time trends in the incidence of scarlet fever showed a bimodal distribution,the fourth quarter of each year was the main peak incidence,with the incidence rate being 5.55/100,000(32.4%),and the second quarter was secondary peak,with the incidence rate of 4.44/100,000(26.0%).The average annual incidence rate in the northwestern central area of Kaifeng City(4.56/100,000)was higher than that in the southeastern suburban area(0.39/100,000),with a statistically significant difference(χ^(2)=864.67,P<0.001).Global spatial autocorrelation analysis revealed that there was a positive spatial correlation in the spatial distribution of incidence rates of scarlet fever in districts and counties,with spatial aggregation(Moran’s I=0.129,P=0.02).Local spatial autocorrelation analysis displayed that there were spatial height-height clustering phenomena in five districts and counties.A total of 33 scarlet fever clusters and 9 outbreaks were reported in Kaifeng City from 2012 to 2022,mainly occurring in kindergartens and primary schools(83.33%),involving 247 cases of scarlet fever(36.43%),and mainly occurring in the fourth quarter(69.05%)and the second quarter(23.81%).Conclusion The regional distribution of incidence rates of scarlet fever in Kaifeng City of Henan Province in 2012-2022 showed spatial clustering characteristics,mainly involving the northwestern central urban area,and the incidence rates of scarlet fever showed a downward trend from north to south and from west to east.The results suggest that targeted preventive and control measures against scarlet fever should be conducted based on the key population in key districts.
作者
仇恒英
张卫文
张洁
王永伟
刘继艳
王喜
QIU Hengying;ZHANG Weiwen;ZHANG Jie;WANG Yongwei;LIU Jiyan;WANG Xi(Kaifeng Municipal Center for Disease Control and Prevention,Kaifeng,Henan 475000,China)
出处
《实用预防医学》
CAS
2024年第3期270-273,共4页
Practical Preventive Medicine
关键词
猩红热
流行病学特征
空间分布
<3636><810:scarlet fever
epidemiological characteristic
spatial distribution