Epidemiological characteristics and trend prediction of scarlet fever in Hubei Province from 2010 to 2018
10.16462/j.cnki.zhjbkz.2020.02.003
- Author:
Jing CAI
1
;
Shu-qiong HUANG
;
Wen-wen YANG
;
Peng ZHANG
;
Cong XIE
;
Ran WU
Author Information
1. Institute of Preventive Medicine Information, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
- Publication Type:Research Article
- Keywords:
Scarlet fever;
Hubei Province;
Epidemiological characteristics;
Incidence trend
- From:
Chinese Journal of Disease Control & Prevention
2020;24(2):134-138,150
- CountryChina
- Language:Chinese
-
Abstract:
Objective To provide reference for formulating scarlet fever prevention and control strategies by analyzing the epidemiological characteristics and predicting the incidence trend of scarlet fever. Methods Spearman correlation analysis, clustering analysis, seasonal index model and seasonal ARIMA model were used for analysis and prediction. Results The average annual incidence of scarlet fever in 2010-2018 was 1.37/100 000, and there was a positive correlation between annual incidence and year (rs=0.817,P=0.007). April-June and November-December were high incidence months. The clustering analysis was significant(F=4795.30，P<0.001), showing that the high-incidence areas are Shennongjia, Yichang, Enshi, Wuhan. Reported cases were concentrated in 1-14 years old, mainly for students, child care children and scattered children. The incidence rate of males was higher than that of females. The optimal model is ARIMA(0,1,1)(0,1,0)12. The prediction showed that the monthly incidence characteristics of 2019 were consistent with previous years, and the annual incidence rate was 10.22/100 000(95% CI:2.33/100 000-30.43/100 000), which was higher than the incidence of 2018. Conclusions The incidence of scarlet fever in Hubei Province is generally on the rise from 2010 to 2018. The incidence is bimodal. Students are the main disease group. The incidence rate of males is higher. The incidence is mainly concentrated in the mountainous areas of southwest and capital cities. The ARIMA model has a good applicability in the prediction of scarlet fever. The incidence level will continue to rise in 2019, and it is necessary to strengthen monitoring and control measures with reference to epidemiological characteristics.
