2008-2017年银川市猩红热流行特征分析及发病趋势预测
|
摘要
目的分析银川市猩红热的流行特征,并预测短期发病趋势,为制订相应的防控措施提供科学依据。方法采用描述性流行病学方法对2008-2017年银川市猩红热监测数据进行分析,并用自回归移动平均混合模型(autoregressive integrated moving average model,ARIMA)对2018年1月至2019年6月猩红热的发病趋势进行预测。结果 2008-2017年银川市共报告猩红热病例5 206人,年均发病率为26.80/10万,整体呈上升趋势。男女发病率比为1.63∶1;3～7岁学龄前儿童占发病总数的78.56%,其中又以5岁儿童发病数最高。金凤区年均发病率(40.97/10万)最高,兴庆区累计发病数最多(2 474例)。发病高峰为4-6月和11月至次年1月。ARIMA模型预测结果显示2018年1月至2019年6月银川市猩红热呈现较高发病水平。结论 2008-2017年银川市猩红热的发病呈上升趋势,应针对托幼机构和小学等高发场所做好预防和控制工作。2018年1月至2019年6月仍是猩红热的高流行期,应做好主要流行区的监测和防控工作。
Objective To analyze the epidemiological characteristics of scarlet fever in Yinchuan City,to predict short-term incidence trend,and to provide a scientific basis for prevention and control.Methods Descriptive epidemiologic method was used to analyze the epidemiological characteristics of scarlet fever in Yinchuan City from 2008 to 2017,and the Autoregressive Integrated Moving Average(ARIMA)model was used to forecast the incidence trend from January 2018 to June 2019.Results A total of 5 206 scarlet fever cases were reported and the average annual incidence was 26.80/100 000 from 2008 to 2017,which showed an upward trend.The incidence ratio of male to female was 1.63∶1,children aged 3-7 years accounted for 78.56%,and most of the cases were found in children aged 5 years.The average annual incidence rate in Jinfeng District was the highest(40.97/100 000).Xingqing District had the largest numbers of cumulative cases(2 474).The incidence peaks were mainly from April to July and from November to January.ARIMA model predicted that the incidence of scarlet fever in Yinchuan City would remain high from January 2018 to June 2019.Conclusion The incidence of scarlet fever in Yinchuan City shows an upward trend from 2008 to 2017.We should pay close attention to high incidence sites including kindergartens and schools to control scarlet fever.January 2018 to June 2019 will be still a period of high morbidity of scarlet fever in Yinchuan City.Therefore,surveillance and control should be continually strengthened in the main epidemic areas.
Objective To analyze the epidemiological characteristics of scarlet fever in Yinchuan City,to predict short-term incidence trend,and to provide a scientific basis for prevention and control.Methods Descriptive epidemiologic method was used to analyze the epidemiological characteristics of scarlet fever in Yinchuan City from 2008 to 2017,and the Autoregressive Integrated Moving Average(ARIMA)model was used to forecast the incidence trend from January 2018 to June 2019.Results A total of 5 206 scarlet fever cases were reported and the average annual incidence was 26.80/100 000 from 2008 to 2017,which showed an upward trend.The incidence ratio of male to female was 1.63∶1,children aged 3-7 years accounted for 78.56%,and most of the cases were found in children aged 5 years.The average annual incidence rate in Jinfeng District was the highest(40.97/100 000).Xingqing District had the largest numbers of cumulative cases(2 474).The incidence peaks were mainly from April to July and from November to January.ARIMA model predicted that the incidence of scarlet fever in Yinchuan City would remain high from January 2018 to June 2019.Conclusion The incidence of scarlet fever in Yinchuan City shows an upward trend from 2008 to 2017.We should pay close attention to high incidence sites including kindergartens and schools to control scarlet fever.January 2018 to June 2019 will be still a period of high morbidity of scarlet fever in Yinchuan City.Therefore,surveillance and control should be continually strengthened in the main epidemic areas.
引文
[1] 郭舫茹,何月莹,白云,等.1983-2011年北京市石景山区猩红热流行特征分析[J].疾病监测,2012(9):702-704.
[2] 宁少奇,陈飒,曹磊,等.陕西省2010-2016年猩红热流行特征分析及趋势预测[J].中华疾病控制杂志,2018,22(6):585-589.
[3] 张漫,杨兴华,吴双胜,等.2010-2016年北京市猩红热流行状况及其危险因素分析[J].疾病监测,2018,33(7):580-584.
[4] 陈伟,赵晓静,张杰,等.河南省2005-2014年猩红热流行特征分析[J].中华疾病控制杂志,2016(1):9-12.
[5] 肖岩.营口市2005-2014年猩红热流行特征[J].中国实用医药,2016,11(34):196-198.
[6] 李雷雷,蒋希宏,隋霞,等.中国2005-2011年猩红热疫情流行病学分析[J].中国公共卫生,2012,28(6):826-827.
[7] Lau EH,Nishiura H,Cowling BJ,et al.Scarlet fever outbreak,Hong Kong,2011[J].Emerging Infectious Diseases,2012,18(10):1700-1702.
[8] Hsieh YC,Huang YC.Scarlet fever outbreak in Hong Kong,2011[J].Journal of Microbiology,Immunology,and Infection,2011,44(6):409-411.
[9] 王洪丽,于琎,江洪.银川市兴庆区2007-2014年传染病流行和变化趋势分析[J].宁夏医科大学学报,2015,37(12):1433-1436.
[10] 秦颖,冯录召,余宏杰.2015年春夏季全国猩红热疫情流行病学特征分析[J].疾病监测,2015,30(12):1002-1007.
[11] 王玲,张玲,王涛,等.淄博市1956-2014年猩红热发病趋势和流行特征[J].中华疾病控制杂志,2016(4):349-352.
[12] 贾伟华,闫芮,李国伟.郑州市2007-2016年猩红热流行特征分析[J].华南预防医学,2018,44(2):144-146.
[13] 耿玉芝,丁乙.新泰市2008-2017年猩红热流行病学特征分析[J].微生物学免疫学进展,2018,46(4):59-62.
[14] 高丽,王骥涛,赵启玉.太原市2011-2016年猩红热流行特征分析[J].山西医药杂志,2018,47(13):1590-1591.
[15] 苏健婷,王超,高燕琳,等.北京市2007-2016年猩红热流行病学特征分析[J].中华疾病控制杂志,2018,22(8):846-848.
[16] 潘欢弘,刘晓青,杨梦,等.2004-2014年江西省猩红热流行特征分析[J].现代预防医学,2016,43(4):577-579,587.
[17] 胡晓雯,倪伟,潘蓓,等.青岛市气象因素对儿童猩红热发病的影响[J].中国学校卫生,2018,39(6):878-880.
[18] 卢志慧,饶丰,袁汝钊,等.2005-2017年东莞市猩红热流行特征分析[J].华南预防医学,2018,44(5):449-452.
[19] 苏淑飞.2006-2015年某市猩红热的流行特征分析[J].中国医药指南,2018,16(29):160-161.
[20] 马合金.2010-2014年承德市猩红热流行病学分析[J].职业与健康,2016(2):208-210.
[21] 于玮莹,彭月华.吉林省2010-2015年猩红热流行病学特征分析[J].中国卫生工程学,2016,15(3):288,291.
[22] 马昭君,营亮.2004-2013年连云港市猩红热流行的特征[J].职业与健康,2015,31(3):348-350.
[23] 李羽敏,付仁仙,董升草.丽水市2004-2013年猩红热流行特征分析[J].上海预防医学,2014(6):293-294.
[24] 霍爱梅,赵达生,方立群,等.华北地区主要呼吸道传染病与气象条件的关系[J].中国医药导报,2011,8(32):153-156,封3.
[25] 黎景雪,王培承,房刚.山东省猩红热发病与气象因素相关性研究[J].中国预防医学杂志,2011(2):149-151.
[26] 王炳翔,朋文佳,闫军伟,等.猩红热的发病率与气象因素的负二项回归分析[J].中华疾病控制杂志,2014(2):166-168.
[27] 王园园,陈伟,李望晨,等.基于ARIMA的传染病发病率趋势预测模型实证研究[J].中国城乡企业卫生,2017(11):6-9.
[2] 宁少奇,陈飒,曹磊,等.陕西省2010-2016年猩红热流行特征分析及趋势预测[J].中华疾病控制杂志,2018,22(6):585-589.
[3] 张漫,杨兴华,吴双胜,等.2010-2016年北京市猩红热流行状况及其危险因素分析[J].疾病监测,2018,33(7):580-584.
[4] 陈伟,赵晓静,张杰,等.河南省2005-2014年猩红热流行特征分析[J].中华疾病控制杂志,2016(1):9-12.
[5] 肖岩.营口市2005-2014年猩红热流行特征[J].中国实用医药,2016,11(34):196-198.
[6] 李雷雷,蒋希宏,隋霞,等.中国2005-2011年猩红热疫情流行病学分析[J].中国公共卫生,2012,28(6):826-827.
[7] Lau EH,Nishiura H,Cowling BJ,et al.Scarlet fever outbreak,Hong Kong,2011[J].Emerging Infectious Diseases,2012,18(10):1700-1702.
[8] Hsieh YC,Huang YC.Scarlet fever outbreak in Hong Kong,2011[J].Journal of Microbiology,Immunology,and Infection,2011,44(6):409-411.
[9] 王洪丽,于琎,江洪.银川市兴庆区2007-2014年传染病流行和变化趋势分析[J].宁夏医科大学学报,2015,37(12):1433-1436.
[10] 秦颖,冯录召,余宏杰.2015年春夏季全国猩红热疫情流行病学特征分析[J].疾病监测,2015,30(12):1002-1007.
[11] 王玲,张玲,王涛,等.淄博市1956-2014年猩红热发病趋势和流行特征[J].中华疾病控制杂志,2016(4):349-352.
[12] 贾伟华,闫芮,李国伟.郑州市2007-2016年猩红热流行特征分析[J].华南预防医学,2018,44(2):144-146.
[13] 耿玉芝,丁乙.新泰市2008-2017年猩红热流行病学特征分析[J].微生物学免疫学进展,2018,46(4):59-62.
[14] 高丽,王骥涛,赵启玉.太原市2011-2016年猩红热流行特征分析[J].山西医药杂志,2018,47(13):1590-1591.
[15] 苏健婷,王超,高燕琳,等.北京市2007-2016年猩红热流行病学特征分析[J].中华疾病控制杂志,2018,22(8):846-848.
[16] 潘欢弘,刘晓青,杨梦,等.2004-2014年江西省猩红热流行特征分析[J].现代预防医学,2016,43(4):577-579,587.
[17] 胡晓雯,倪伟,潘蓓,等.青岛市气象因素对儿童猩红热发病的影响[J].中国学校卫生,2018,39(6):878-880.
[18] 卢志慧,饶丰,袁汝钊,等.2005-2017年东莞市猩红热流行特征分析[J].华南预防医学,2018,44(5):449-452.
[19] 苏淑飞.2006-2015年某市猩红热的流行特征分析[J].中国医药指南,2018,16(29):160-161.
[20] 马合金.2010-2014年承德市猩红热流行病学分析[J].职业与健康,2016(2):208-210.
[21] 于玮莹,彭月华.吉林省2010-2015年猩红热流行病学特征分析[J].中国卫生工程学,2016,15(3):288,291.
[22] 马昭君,营亮.2004-2013年连云港市猩红热流行的特征[J].职业与健康,2015,31(3):348-350.
[23] 李羽敏,付仁仙,董升草.丽水市2004-2013年猩红热流行特征分析[J].上海预防医学,2014(6):293-294.
[24] 霍爱梅,赵达生,方立群,等.华北地区主要呼吸道传染病与气象条件的关系[J].中国医药导报,2011,8(32):153-156,封3.
[25] 黎景雪,王培承,房刚.山东省猩红热发病与气象因素相关性研究[J].中国预防医学杂志,2011(2):149-151.
[26] 王炳翔,朋文佳,闫军伟,等.猩红热的发病率与气象因素的负二项回归分析[J].中华疾病控制杂志,2014(2):166-168.
[27] 王园园,陈伟,李望晨,等.基于ARIMA的传染病发病率趋势预测模型实证研究[J].中国城乡企业卫生,2017(11):6-9.