热带病与寄生虫学 ›› 2020, Vol. 18 ›› Issue (1): 33-36.

• 论著 • 上一篇    下一篇

Logistic 微分方程模型在结核病疫情预警中的应用

王明斋1 , 余珊珊2 , 芮佳2 ,杨蒙2 ,王瑶2 , 王琦琦3 , 陈田木2 , 郑蓉蓉1∗, 张小芬2∗   

  1. 1. 厦门市疾病预防控制中心,厦门 361021; 2. 分子疫苗学和分子诊断学国家重点实验室,厦门大学公共卫生学院; 3. 中国疾病预防控制中心
  • 收稿日期:2019-11-25 出版日期:2020-03-10 发布日期:2020-03-10
  • 通信作者: ∗通讯作者,郑蓉蓉,E-mail:rong3018@163.com;张小芬,E-mail:phenyzhang@xmu.edu.cn
  • 作者简介:王明斋,男,硕士,主管医师,研究方向:传染病预防控制和突发事件卫生应急。 E-mail:32639937@qq.com
  • 基金资助:
    厦门市科技计划指导性项目(2010S0658);厦门大学大学生创新创业训练计划项目(2019Y0805);福建省自然科学基 金(2016J05202)

Logistic differential equation model and its application in warning tuberculosis

WANG Ming- zhai1 , YU Shan - shan2 , RUI Jia2 , YANG Meng2 , WANG Yao2 , WANG Qi - qi3 , CHEN Tian - mu2 , ZHENG Rong-rong1∗ ,ZHANG Xiao-fen2∗   

  1.  1. Xiamen Center for Disease Control and Prevention, Xiamen 361021, China; 2. State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health of Xiamen University; 3. Chinese Center for Disease Control and Prevention
  • Received:2019-11-25 Online:2020-03-10 Published:2020-03-10
  • Contact: ∗Corresponding author, E-mail:rong3018@163.com; phenyzhang@xmu.edu.cn

摘要: 目的 利用 Logistic 微分方程模型进行结核病传播预测,为结核病早期防控特别提供新方法。 方法 对 Logistic 微分方程模型的原理、疫情加速关键点计算、优缺点等进行分析,以厦门市报告数据为例开展模拟研究。 结果 厦门市自 2005-2018 年来结核病高发,存在明显的冬春季节流行高峰。 通过 Logistic 微分方程拟合结果较好,疫 情加速期为每年第 1 或第 2 个月。 结论 Logistic 微分方程模型能较好地反映结核病“疫情加速时间”和“建议预警 时间”,以及疫情变化的时间点,对于基层开展结核病预警防控工作,具有较好的参考意义。

关键词: Logistic微分方程, 数学模型, 结核病, 暴发

Abstract: Objective To apply the logistic differential equation (LDE) model to predicting the spread of tuberculosis for a new method in early prevention and control of tuberculosis. Methods The principle of LDE model, calculation of the critical points at accelerated epidemic, advantages and disadvantages were analyzed, and simulation investigation was per- formed on the data reported in Xiamen City basis. Results Tuberculosis was highly prevalent in Xiamen from 2005 to 2018, typically characterized by wave in winter and spring seasons. LDE model resulted in well fitting to the prevalence. Accelera- tion of the epidemic was identified in the first or the second month of the previous years. Conclusion LDE model can better reflect the acceleration trend and initiation of warning of tuberculosis prevalence in early stage as well as the changing point of the epidemic, which should be a better tool for health workers in prevention, control and warning of tuberculosis on grass- root levels.

Key words: Logistic differential equation model, Mathematical model, Tuberculosis, Outbreak

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