ARIMA乘积季节模型及其在传染病发病预测中的应用

本文研究乘积季节模型在传染病发病情况预测中的应用,并探讨提高模型准确性和实用性的途径.以1980年1月至2000年7月江苏省肾综合征出血热发病资料建立模型,以2000年的发病资料作为模型预测效果的考核样本.首先采用差分方法对序列资料进行平稳化,然后进行定阶并估计参数,建立乘积季节模型,最后对预测结果进行检验和分析.从而更好地掌握未来疫情动态发展趋势.检验结果表明,用乘积季节模型对肾综合征出血热月发病情况的拟合结果满意,预测效果良好.     

对全国法定传染病发病率趋势进行预测

目的　研究全国法定传染病的发病规律和趋势。方法　对于1990———2001年资料完整的20种传染病,借助MATLAB6 1版本数学软件编程,建立灰色系统G(1,1)模型,并进行外推3年预测。结果　后验差比值C和小误差概率P综合模型检验,20个模型等级结果是:9个1级、8个2级、3个3级。结论　通过模型进行分析,除淋病、布氏杆菌病、斑疹伤寒3种近期未来发病率将上升外,其余17种发病率近期未来将下降。     

具移民输入和时空时滞的非局部扩散传染病模型的行波解

针对种群个体在疾病传播期间自由移动的现象,建立了具有移民输入,时滞和空间扩散的非局部扩散传染病模型.利用基本再生数和最小波速作为行波解是否存在的判别变量,利用Schauder不动点定理证明行波解的存在性,为传染病控制和预测提供一些理论依据.     

基于白噪声的网络传染病模型动力学分析北大核心CSCD

该文基于确定性网络传染病模型,建立了白噪声影响下的随机网络传染病模型,证明了模型全局解的存在唯一性,利用随机微分方程理论得到了传染病随机灭绝和随机持久的充分条件.结果表明,白噪声对网络传染病传播动力学有很大的影响,白噪声能有效抑制传染病的传播,大的白噪声甚至能让原本持久的传染病变得灭绝.最后,通过数值模拟验证了理论结果.     

流行性感冒的微分方程模型及数据分析

流行性感冒作为一种传染病,至今仍然经常爆发,对人们正常的工作、生活造成严重影响.依据流感的传染方式及观测数据,通过建立常微分方程模型,可探讨流感的传播规律、影响它流行的因素、预测可能发生的流行及如何抑制其流行.     

基于三类模型的四大银行股票收益率预测研究

运用时间序列分析的预测方法,对四大银行的股票日对数收益率序列进行拟合与预测分析,分别构建ARMA模型、GARCH模型以及ARMA-GARCH组合模型,通过模型比较,实证分析表明:在拟合效果上,ARMA-GARCH模型的拟合优度优于ARMA模型和GARCH模型;在预测效果上,ARMA模型的预测效果最优,ARMA-GARCH模型次之.     

传染病模型的拓展与计算

以经典传染病模型为例,清晰解读模型构造思想,将建模思想应用于埃博拉病毒传播中,拓展传染病模型,并从连续角度和离散角度阐述传染病模型求解技巧。模型的构造思想和求解技术可自然推广至经济模型、人口模型等问题中。     

传染病增长中的几个数学模型

某国家某种传染病的发病数呈上升趋势 ,统计近四年这种病的新发病人数如下表所示 ,如果不加控制 ,将仍按这个趋势发展下去 .请预测从 2 0 0 3年初到 2 0 0 6年底的四年里 ,该国家该传染病的新发病总人数 .年　份 19992 0 0 0 2 0 0 12 0 0 2新发病人数 2 4 0 0 2 4 912 5 86 2 6 84分析　这是对一份统计资料进行分析 ,把握其规律建立合理的数学模型 ,对其进行定量分析是解决问题的关键 .思路 1　建立传染病增长率模型由上表数据可知 ,1999～ 2 0 0 0年该病的增长率为 2 4 91- 2 4 0 02 4 0 0 3.792 .同理可得 ,2 0 0 0～ 2 0 0 1年 ,2 0 …     

离散SCIRS模型在我国流脑中的应用（英文）

本文研究一类离散SCIRS模型的动力学性态,利用再生矩阵的方法得到模型的基本再生数,证明模型无病平衡点的全局渐近稳定性,以及模型地方病平衡点的存在性与一致持续性.数值模拟显示地方病平衡点可能是全局渐近稳定的.最后,把模型应用到我国流脑的传播中,通过数值模拟的结果和法定传染病报告的结果对比,表明该模型在一定程度上可以用来预测流脑在我国的传播.     

上海股市波动的预测方式和模型

探讨基于 SV类模型的上海股市波动的预测方式和模型问题 .比较了 SV( stochastic volatility)类模型 (包括基本 SV模型和 ASV模型 )在两种不同方式下的预测效果 ,并将基本 SV类模型的预测效果与 ASV模型 ,以及其他常用模型做了比较 .结果表明 :SV类模型在两种预测方式下的预测效果存在一定的差异 ;基本 SV模型对于上海股市具有较强的预测能力 ;ASV模型的预测效果不理想 .     

关于SARS病毒传播的马尔可夫骨架过程模型

根据SARS病毒传播的特性和侯振挺等人提出的马尔可夫骨架过程理论，建立了SARS病毒传播的马尔可夫骨架模型，并得出结论，在任一时刻的疑似病例数，传染病人数是某非负线性方程组的最小非负解。     

Analysis of a stochastic recovery-relapse epidemic model with periodic parameters and media coverage

This paper addresses, motivated by mathematical work on infectious disease models, the impacts of environmental noise and media coverage on the dynamics of recovery-relapse infectious diseases. A susceptible-infectious-recovered-infectious model is formulated with both vertical transmission and horizontal transmission. The existence and uniqueness of the positive global solution is studied by constructing suitable Lyapunov-type function. Then, the existence of positive periodic solutions is verified by applying Khasminskii"s theory. The existence of positive periodic solutions indicates the continued survival of the diseases. Besides, sufficient conditions for the extinction of the diseases are obtained. Numerical simulations then demonstrate the dynamics of the solutions. The paper extends the results of the corresponding deterministic system.     

Spreading speed for a nonlocal dispersal vaccination model with general incidence

This paper is concerned with the spreading speed for a nonlocal dispersal vaccination model with general incidence. We first prove the existence and uniform boundedness of solutions for this model by using the Schauder’s fixed point theorem. Then, applying comparison principle, we establish the existence of spreading speed for the infective individuals. According to our result, one can see that the spreading speed coincides with the critical speed of traveling wave solution connecting the disease-free and endemic equilibria. In addition, the diffusion rate of the infected individuals can increase the spread of infectious diseases, while the vaccination rate reduces the spread of infectious diseases.     

Approximating individual risk of infection in a Markov chain epidemic network model with a deterministic system

In the Markov chain model of infectious diseases in a connected network of heterogeneous individuals, the computation of the risk of infection for each individual and the expected size of the infected population over time is an NP-hard problem. We show that the individual risk of infection over time can be approximated by orbits of a nonlinear discrete dynamical system on a phase space of dimension equal to the number of individuals in the network. An upper bound for the eradication rate of the infectious disease in the network is also obtained.     

A generalized infectious model induced by the contacting distance (CTD)

The aim of this paper is to theoretically study the effect of the contacting distance (CTD) between the susceptible and infectious individuals in controlling infectious diseases. This paper formulates a generalized SEIR model incorporating the effect of the contacting distance (CTD). The dynamical behaviors of the proposed model are investigated and the controlling measures of the infectious diseases are developed. The results show that the contacting distance (CTD) between the susceptible and infectious individuals plays an important role in controlling infectious diseases. Some diseases will be globally controlled when the contacting distance (CTD) is larger than the threshold value. That is to say, the long contacting distance (CTD) implies the corresponding diseases will be controlled. However, for other diseases, the long or short contacting distance (CTD) will induce them to spread and be endemic. The moderate contacting distance (CTD) may be beneficial to control these diseases. Therefore, the appropriate contacting distance (CTD) should be selected for the given diseases in order to control the corresponding infectious diseases. Finally, a special numerical experiment is given to test our results. These results give some theoretical and experimental guides for the disease control authorities.     

新增股民数量增长模式分析

考虑到传染病的传播与股民数量的增长之间的类似性,建立了刻画新增股民数量变化规律的数学模型,并进行了相应的数学实验.建立的模型较好地反映了短期内新增股民数量的变化规律.     

Modelling the spread of bacterial disease: effect of service providers from an environmentally degraded region

In this paper, an SIS model for bacterial infectious diseases, like tuberculosis, typhoid, etc., caused by direct contact of susceptibles with infectives as well as by bacteria is proposed and analyzed. Here the demography of the human population is constant immigration and the cumulative rate of the environmental discharges is a function of total human population. Further this model is extended to the model for socially structured population (rich and poor) where poor people work as service provider in the houses of rich people but do not settle in the habitat of rich people. It is assumed that bacteria population does not survive in the clean environment of rich people and only affects the population in the degraded environment of the poor class. The stability of the equilibria is studied by using the theory of differential equation and computer simulation. It is concluded that the spread of the infectious disease increases when the growth of bacteria caused by conducive environmental discharge due to human sources increases. Also the spread of the infectious disease in rich class increases due to the interaction with service providers, who are living in relatively poor environmental condition, suggesting the need to keep our environment clean all around.     

K-means聚类算法在SIR传染病模型中的应用研究

基于SIR传染病模型,建立了具有K-means聚类算法的SIR元胞自动机模拟模型.通过对分别服从高斯分布和随机均匀分布的两类初始感染源的分析与模拟,给出了疾病感染半径与隔离半径对疾病传播的影响.结果显示:在两种不同类型的初试分布下,感染者的最大值分别与疾病感染传播半径和隔离半径呈正相关与负相关关系,感染者数量随时间的变化率亦呈现相同的变化规律.初始数据的不同分布类型只影响这种正负相关关系的增速.研究结果可为控制和消除传染病提供有效合理的隔离措施,为卫生部门提供防控传染病的理论支持.     

Effects of population density on the spread of disease

The effect of population density on the epidemic outbreak of measles or measles-like infectious diseases was evaluated. Using average-number contacts with susceptible individuals per infectious individual as a measure of population density, an analytical model for the distribution of the nonstationary stochastic process of susceptible contact is presented. A 5-dimensional lattice simulation model of disease spread was used to evaluate the effects of four different population densities. A zero-inflated Poisson probability model was used to quantify the nonstationarity of the contact rate in the stochastic epidemic process. Analysis of the simulation results identified a decrease in a susceptible contact rate from four to three, resulted in a dramatic effect on the distribution of contacts over time, the magnitude of the outbreak, and, ultimately, the spread of disease. © 2001 John Wiley & Sons, Inc.