Objective To understand the characteristics and epidemic trend of scarlet fever in Hefei City,and to provide scientific prevention and control strategies and measures. Methods Download the data 4 340 cases of scarlet fever cases in Hefei City from 2011 to 2023 from the China Infectious Disease Reporting Information Management System,organize and statistically analyze them using Excel,and construct an ARIMA model for predicting the incidence trend. Results A total of 4 340 cases of scarlet fever were reported in Hefei City from 2011 to 2023,with an average annual reported incidence rate of 4.23/100 000,and no deaths were reported.The overall trend curve for 2023 was similar to that of 2011-2016,2017-2019,and 2020-2022,with two peaks occurring in May June and November December.Since 2011,there had been a peak outbreak every 2-4 years.From 2011 to 2023,scarlet cases were reported in 9 counties (cities and districts) in Hefei City,and the annual average reported incidence rate in municipal districts (705/100 000) was higher than that in rural areas (1.62/100 000).The high incidence of scarlet fever in Hefei City was among children aged 3 to 9 years old.The average annual reported incidence rate of male (5.22/100 000) was higher than that of female (3.19/100 000).ARIMA model predicted that the monthly reported incidence rate of scarlet fever in Hefei City in 2024 (3.67/100 000) and the number of cases (354 cases) would increase compared with 2023,in January,May-July and December,the reported incidence rate had a fluctuating peak. Conclusion In 2024,the incidence of scarlet fever in Hefei City may show an upward trend.It is recommended to strengthen multi-channel monitoring and early warning,pay attention to the population of children in lower grades of primary schools and preschool children in urban areas,and be alert to the risk of a resurgence of the epidemic in schools during the peak period of the epidemic.
Key words
Scarlet fever /
Epidemiological characteristics /
Trend prediction
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 李群.传染病学[M].2版.北京:人民卫生出版社,2013.
[2] Wong SS,Yuen KY.Streptococcus pyogenes and re-emergence of scarlet fever as a public health problem[J].Emerg Microbes Infect,2012,1(7):e2.
[3] Lamagni T,Guy R,Chand M,et al.Resurgence of scarlet fever in England,2014-16:a population-based surveillance study[J].Lancet Infect Dis,2018,18(2):180-187.
[4] 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.
[5] 马涛,洪镭,杜雪飞,等.2014—2019年南京市猩红热流行特征和时空聚集性[J].中华疾病控制杂志,2021,25(3):346-351.
[6] 袁璐,张元元,房明,等.2014—2018年中国猩红热时空聚集性分析[J].现代预防医学,2022,49(22):4033-4038.
[7] 寇玲玲,王国栋,李思瑶,等.西安市2011—2020年猩红热流行病学特征分析[J].现代预防医学,2021,48(23):4245-4248+4271.
[8] 刘军,刘建华,王蕾,等.宜昌市2004—2022年猩红热流行特征分析[J].海峡预防医学杂志,2023,29(5):2+111.
[9] Li C,Liao R,Zhu W,et al.Spatiotemporal dynamics and potential ecological drivers of acute respiratory infectious diseases:an example of scarlet fever in Sichuan Province[J].BMC Public Health,2022,22(1):2139.
[10] 谭小华,刘美真,杨宇威,等.2005—2017年广东省猩红热流行特征分析[J].疾病监测,2019,5(5):411-416.
[11] 刘剑锋,师欢,张捷,等.2014—2021年榆林市猩红热流行特征分析[J].医学动物防制,2023,39(5):490-493.
[12] 刘维量,寇增强,房明,等.2008—2017年山东省猩红热流行病学特征分析[J].现代预防医学,2019,46(1):9-13.
[13] 王秀琴,王芳,马金宇,等.2011—2021年宁夏猩红热流行病学特征分析[J].宁夏医科大学学报,2023,45(9):941-945.
[14] 张俊青,吴金菊,刘怀珠.合肥市2004—2007年猩红热病例分布的流行病学分析[J].安徽预防医学杂志,2008(3):181-182.
[15] 马春娜,吴双胜,段玮,等.2017—2020年北京市猩红热流行病学特征及监测系统代表性分析[J].实用预防医学,2022,8(12):1435-1438.
[16] Chen H,Chen Y,Sun B,et al.Epidemiological study of scarlet fever in Shenyang,China[J].BMC Infect Dis,2019,19(1):1074.
[17] 赵庆龙,刘诗蒙,李美娜,等.2010—2019年吉林省猩红热流行特征分析[J].热带病与寄生虫学,2020,18(3):155-158.
[18] 罗朝晨,翁顺太,谢芳钦,等.2011—2020年福建省猩红热流行特征分析[J].预防医学论坛,2021,27(10):784-786+790.
[19] 崔朋伟,杭惠,陈立凌.2010—2019年苏州市猩红热流行病学特征[J].江苏预防医学,2021,32(3):329-330.
[20] 王蕾,王文娟,韩红,等.2010—2020年太原市猩红热流行病学特征分析[J].中国公共卫生管理,2023,39(2):265-267.