广东省恙虫病流行特征及发病风险预测

doi:10.11853/j.issn.1003.8280.2021.03.015

中国媒介生物学及控制杂志 ›› 2021, Vol. 32 ›› Issue (3): 334-338.DOI: 10.11853/j.issn.1003.8280.2021.03.015

广东省恙虫病流行特征及发病风险预测

李文¹, 马德龙², 赵嘉欣¹, 母群征¹, 李贵昌¹, 刘小波¹, 王君¹, 张钦凤², 刘起勇¹, 鲁亮¹

1. 中国疾病预防控制中心传染病预防控制所媒介生物控制室, 传染病预防控制国家重点实验室, 北京 102206;
2. 山东第一医科大学公共卫生学院, 山东泰安 271016

收稿日期:2020-12-15 出版日期:2021-06-20 发布日期:2021-06-20
通讯作者: 鲁亮,E-mail:luliang@icdc.cn
作者简介:李文,女,在读硕士,主要从事气象敏感性传染病研究工作,E-mail:xiaosheili@163.com
基金资助:
科技基础调查专项（2017FY101202）；国家卫生健康委委托项目（气候变化健康风险评估策略与技术研究）

Epidemiological characteristics and risk prediction of scrub typhus in Guangdong province, China

LI Wen¹, MA De-long², ZHAO Jia-xin¹, MU Qun-zheng¹, LI Gui-chang¹, LIU Xiao-bo¹, WANG Jun¹, ZHANG Qin-feng², LIU Qi-yong¹, LU Liang¹

1. State Key Laboratory of Infectious Diseases Prevention and Control, Department of Vector Biology and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China;
2. School of Public Health, Shandong First Medical University, Tai'an, Shandong 271016, China

Received:2020-12-15 Online:2021-06-20 Published:2021-06-20
Supported by:
Supported by the Science and Technology Resources Survey (No. 2017FY101202) and National Health Commission-commissioned Research (Strategy and Technology Research on Climate Change Health Risk Assessment)

摘要/Abstract

摘要：

目的分析2012－2018年广东省恙虫病流行特征及变化趋势，预测其发病趋势，为评价恙虫病防控措施提供科学依据。方法收集2012－2018年广东省恙虫病病例信息，进行描述性流行病学分析，并应用时间序列基于季节性差分的自回归积分移动平均模型（ARIMA）建立预测模型，比较2019年的观察值和预测值评估模型，预测2020年发病情况。结果 2012－2018年广东省共报告恙虫病病例33 490例，发病呈逐年增加的趋势，主要集中在6－10月；50～60岁年龄组病例数最多，女性病例数多于男性，农民发病占比最高（65.49%）；使用月度恙虫病病例数据拟合ARIMA模型为（1，1，1）（0，1，1）₁₂，贝叶斯信息准则（BIC）为879.36，Ljung-Box统计量检验残差序列为白噪声序列，调整R²=0.377，模型拟合效果较好，2019年实际值基本在预测值的95%可信区间内，模型预测效果较好。结论广东省恙虫病有逐年增加的趋势，主要发病人群为50～60岁、女性、农民，ARIMA模型能够较好地预测广东省恙虫病病例的变化情况，提示有关部门应在恙虫病高发季节加强重点人群的宣传教育和疫情防控。

关键词: 恙虫病, 流行特征, 自回归积分移动平均模型

Abstract:

Objective To analyze the epidemiological characteristics and changing trend of scrub typhus cases in Guangdong province, China from 2012 to 2018, to predict the incidence trend, and to provide a scientific basis for evaluating the prevention and control measures of scrub typhus. Methods The data of scrub typhus cases in Guangdong province from 2012 to 2018 were collected. A descriptive epidemiological analysis was conducted. A seasonal autoregressive integrated moving average (ARIMA) time series model was used to establish a forecasting model, which was evaluated by comparing the observed and predicted values in 2019, and the incidence of scrub typhus in Guangdong province in 2020 was predicted using the model. Results A total of 33 490 scrub typhus cases were reported in Guangdong province from 2012 to 2018, with the incidence increasing year by year, and the cases mainly occurred in June to October. The incidence was highest in the 50-60 years group; there were more cases in females than in males, and farmers (65.49%) were the dominant occupation. The ARIMA (1,1,1)(0,1,1)₁₂ model was fitted with the monthly case data; the Bayesian information criterion was 879.36; the residual sequence was white noise sequence according to the Ljung-Box test, and the adjusted R² value was 0.377. The fitting effect of the model was good. The actual value in 2019 was basically consistent with the predicted value with 95% confidence interval; the model had a good predictive effect. Conclusion The scrub typhus incidence shows an increasing trend year by year in Guangdong province. The main susceptible populations were people aged 50-60 years, females, and farmers. The ARIMA model can be used to predict the changes in scrub typhus cases in Guangdong province well, suggesting that the relevant departments should strengthen the publicity and education of key population and the epidemic prevention and control in the season with high incidence of scrub typhus.

Key words: Scrub typhus, Epidemiological characteristics, Autoregressive integrated moving average model

中图分类号:

R376⁺.2

李文, 马德龙, 赵嘉欣, 母群征, 李贵昌, 刘小波, 王君, 张钦凤, 刘起勇, 鲁亮. 广东省恙虫病流行特征及发病风险预测[J]. 中国媒介生物学及控制杂志, 2021, 32(3): 334-338.

LI Wen, MA De-long, ZHAO Jia-xin, MU Qun-zheng, LI Gui-chang, LIU Xiao-bo, WANG Jun, ZHANG Qin-feng, LIU Qi-yong, LU Liang. Epidemiological characteristics and risk prediction of scrub typhus in Guangdong province, China[J]. Chines Journal of Vector Biology and Control, 2021, 32(3): 334-338.

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广东省恙虫病流行特征及发病风险预测

Epidemiological characteristics and risk prediction of scrub typhus in Guangdong province, China

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