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防护措施下一类高传染性多潜伏期传染病的高维动态模型
引用本文:谈树萍,张纪峰.防护措施下一类高传染性多潜伏期传染病的高维动态模型[J].生物数学学报,2005,20(4):392-398.
作者姓名:谈树萍  张纪峰
作者单位:中国科学院数学与系统科学研究院,北京,100080
基金项目:国家自然科学基金和科技部重大基础研究前期研究专项资助项目
摘    要:传染病给人们的生命带来了极大的威胁,对于高传染性的疾病,政府总会采取一些防护措施.本文针对防护措施下的高传染性且具有潜伏期等特性的一类传染病,结合传染病模型,在一定假设条件下给出了这类疾病单日新收治的直接确诊病例及疑似病例的高维动态模型,并使用最小二乘法进行了参数辨识.最后以SARS为例,利用网上公布的SARS数据给出了5月22日-5月31日的预测结果并将预测结果和实际数据进行了比较,说明了模型的有效性.

关 键 词:传染病  高维动态模型  参数估计  最小二乘法  预测
文章编号:1001-9626(2005)04-0392-07
收稿时间:2003-06-10
修稿时间:2003年6月10日

A High-Dimensional Propagation Model for a Class of Highly Infectious Latent Diseases under Safety Measures
TAN Shu-ping,ZHANG Ji-feng.A High-Dimensional Propagation Model for a Class of Highly Infectious Latent Diseases under Safety Measures[J].Journal of Biomathematics,2005,20(4):392-398.
Authors:TAN Shu-ping  ZHANG Ji-feng
Institution:Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijin9 100080 China
Abstract:Considering the great threat form infections against people's lives, safety measures are always taken to avoid spreading of highly infectious diseases. In this paper, with respect to a class of highly infectious latent diseases under safety measures, a high-dimensional dynamical model is presented for the daily populations of patients and of suspect patients based on the concepts of previous epidemic model and some mild assumptions Least square algorithm is used to estimate the model parameters. Finally, as an example, the daily number of SARS patients and that of SARS supect patients in Beijing from May 22 to 31 is predicted based on the data opened on network. Comparison of the prediction data with the real data shows the efficiecy of our model
Keywords:Infection  High-dimensional dynamical model  Parameter estimation  Least square algorithm  Prediction
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