新疆麻疹发病情况的ARMA模型预测分析探讨

就新疆近年来麻疹发病情况做了简要分析,针对新疆麻疹发病率高的情况,探讨了ARMA模型预测新疆麻疹发病的可行性,为新疆该病的预防控制工作提供科学参考.     

一类非线性动力系统的数值分析及控制策略研究

根据艾滋病在新疆的流行特点,建立了一个非线性动力系统的数学模型来研究艾滋病在新疆高危人群中传播的规律.通过查阅大量的统计数据和文献资料,确定了模型中部分参数的具体数值,然后通过数据拟合的方法得到了各个高危人群中的HIV病毒的传染性系数.在模型中,选择2004年底(2005年初)作为系统的初始点,预测了艾滋病未来几年内在新疆的流行趋势.最后,提出并比较遏止艾滋病传播的各项干预措施.     

高校科技资源配置效率比较分析

基于数据包络分析(DEA)模型,为讨论高校在不同方面的表现,定义了不同投入产出的四种模型,结果表明不同的投入产出组合会得到不同的效率得分,此外通过不同模型的比较,可以知道十年间新疆高校科研效率的对比情况.为进一步分析新疆高校的科研效率情况,对新疆9所高校的科研效率做了进一步分析,通过对这九所高校的技术及规模效率分析,对高校的进一步发展提出了建议.     

SARIMA模型在新疆手足口病发病率预测中的应用

建立新疆手足口病发病率的季节求和自回归-移动平均模型(Seasonal AutoregressiveIntegrated Moving Average Model,SARIMA),探讨采用SARIMA模型预测手足口病发病趋势的可行性和实用性.利用R统计软件基于新疆2006-2012手足口病月发病率数据建立SARIMA模型,拟合2012年手足口病各月发病率数据,并预测了2013年手足口病月发病率.经过序列平稳化、模型识别以及模型诊断,SARIMA(1,0,1)(0,1,0)_(12)能较好地拟合既往时间段的发病率,且预测值符合新疆手足口病实际发病率的波动趋势.SARIMA模型能够有效地预测手足口病发病趋势,对预警、防控具有积极指导意义.     

行为改变下的艾滋病流行预测

基于亚洲艾滋病流行模型(Asian Epidemic Model,AEM)基本思想,建立我国艾滋病流行预测模型.利用该模型,估计某地1989—2007年艾滋病流行状况,同时设计不同行为改变方案,预测该地2008—2020年艾滋病流行趋势.     

麻疹防治中免疫接种和有效治疗效果比较的建模分析

探讨了H.E.Soper所提出的麻疹模型的解的局部稳定性和全局稳定性,并解释了其生物意义.基于麻疹周期性爆发的特征及其防治方法,作者分别提出了具有免疫接种和有效治疗两种情况下的新模型,并分别对模型进行了分析.比较了两种防控措施的模型分析结果,得到在麻疹的防治工作中有效治疗能够有效控制大规模爆发的结论.     

基于改进灰色GM(1,1)模型的新疆人口总量的分析与预测

利用Lagrange插值理论重构了GM(1,1)预测模型的背景值,以提高改进GM(1,1)模型的预测精度和实效性,进而利用该模型对新疆人口发展态势进行了科学分析与预测.     

基于改进GM(1,1)模型的新疆煤炭消费预测

科学地预测煤炭消费量可为煤炭生产、进口、消费提供可靠的理论依据,建立了1998-2015年新疆煤炭消费的非线性回归的GM(1,1)模型,并预测了2016-2030年的值.研究表明:改进GM(1,1)模型的预测效果良好,新疆煤炭消费量在2016-2030年将持续出现增长趋势,但增速有所下降.     

基于耦合—关联模型的新疆城镇化与农村居民消费结构互动关系研究

研究基于2002-2017年新疆城镇化水平和农村居民消费面板数据,运用耦合协调度模型和灰色关联模型对新疆城镇化(UR)与农村居民消费结构(RCS)"量"与"质"进行综合分析.结果表明:城镇化对农村居民消费结构有强正向拉动作用,但农村居民消费结构对城镇化反向促进作用相对较弱,其中交通通信消费的弱势作用最为显著.研究在模型机理分析的基础上对新疆城镇化发展与消费结构改善升级提出相应对策建议.     

基于灰色预测模型的新疆肺结核疫情分析

借助灰色系统理论对新疆2004-2010年肺结核发病率进行研究,建立不同维度的静态GM(1,1)模型与动态等维递补灰预测模型对数据进行模拟和预测.针对新疆肺结核疫情发病率数据,探索建立新疆肺结核疫情传播预测模型,为肺结核防治提供科学依据.     

Theoretical examination of the pulse vaccination policy in the SIR epidemic model

Based on a theory of population dynamics in perturbed environments, it was hypothesized that measles epidemics can be more efficiently controlled by pulse vaccination, i.e., by a vaccination effort that is pulsed over time [1]. Here, we analyze the rationale of the pulse vaccination strategy in the simple SIR epidemic model. We show that repeatedly vaccinating the susceptible population in a series of ‘pulses,’ it is possible to eradicate the measles infection from the entire model population. We derive the conditions for epidemic eradication under various constraints and show their dependence on the parameters of the epidemic model.     

Novel analytical and numerical techniques for fractional temporal SEIR measles model

In this paper, a fractional temporal SEIR measles model is considered. The model consists of four coupled time fractional ordinary differential equations. The time-fractional derivative is defined in the Caputo sense. Firstly, we solve this model by solving an approximate model that linearizes the four time fractional ordinary differential equations (TFODE) at each time step. Secondly, we derive an analytical solution of the single TFODE. Then, we can obtain analytical solutions of the four coupled TFODE at each time step, respectively. Thirdly, a computationally effective fractional Predictor-Corrector method (FPCM) is proposed for simulating the single TFODE. And the error analysis for the fractional predictor-corrector method is also given. It can be shown that the fractional model provides an interesting technique to describe measles spreading dynamics. We conclude that the analytical and Predictor-Corrector schemes derived are easy to implement and can be extended to other fractional models. Fourthly, for demonstrating the accuracy of analytical solution for fractional decoupled measles model, we applied GMMP Scheme (Gorenflo-Mainardi-Moretti-Paradisi) to the original fractional equations. The comparison of the numerical simulations indicates that the solution of the decoupled and linearized system is close enough to the solution of the original system. And it also indicates that the linearizing technique is correct and effective.     

Mathematical model for assessing the impact of vaccination and treatment on measles transmission dynamics

A deterministic model for the transmission dynamics of measles in a population with fraction of vaccinated individuals is designed and rigorously analyzed. The model with standard incidence exhibits the phenomenon of backward bifurcation, where a stable disease‐free equilibrium coexists with a stable endemic equilibrium whenever the associated reproduction number is less than unity. This phenomenon can be removed if either measles vaccine is assumed to be perfect or disease related mortality rates are negligible. In the latter case, the disease‐free equilibrium is shown to be globally asymptotically stable whenever the associated reproduction number is less than unity. Furthermore, the model has a unique endemic equilibrium whenever the reproduction threshold exceeds unity. This equilibrium is shown, using a nonlinear Lyapunov function of Goh‐Volterra type, to be globally asymptotically stable for a special case.     

Approaches to the space-time modelling of infectious disease behaviour

A new approach to the space-time modelling of infectious diseasesis considered. A modulated heterogeneous Poisson process withintensity defined as a function of a two-dimensional susceptibilityfield is proposed. The model is fitted to a measles epidemicusing a proportional hazards approximation.     

Using CONTENT 1.5 to analyze an SIR model for childhood infectious diseases

In this work, we introduce a standard software CONTENT 1.5 for analysis of dynamical systems. A simple model for childhood infectious diseases is used as an example. The detailed steps to obtain the bifurcation structures of the system are given. These bifurcation structures can be used to explain the observed dynamical transition in measles incidences.     

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.     

Dynamics of SIS Epidemic Model with Varying Total Population and Multivaccination Control Strategies

In this paper, two susceptible‐infected‐susceptible epidemic models with varying total population size, continuous vaccination, and state‐dependent pulse vaccination are formulated to describe the transmission of infectious diseases, such as diphtheria, measles, rubella, pertussis, and so on. The first model incorporates the proportion of infected individuals in population as monitoring threshold value; we analytically show the existence and orbital asymptotical stability of positive order‐1 periodic solution for this control model. The other model determines control strategy by monitoring the proportion of susceptible individuals in population; we also investigate the existence and global orbital asymptotical stability of the disease‐free periodic solution. Theoretical results imply that the disease dies out in the second case. Finally, using realistic parameter values, we carry out some numerical simulations to illustrate the main theoretical results and the feasibility of state‐dependent pulse control strategy.     

Multiple recurrent outbreak cycles in an autonomous epidemiological model due to multiple limit cycle bifurcation

Multiple recurrent outbreak cycles have been commonly observed in infectious diseases such as measles and chicken pox. This complex outbreak dynamics in epidemiologicals is rarely captured by deterministic models. In this paper, we investigate a simple 2-dimensional SI epidemiological model and propose that the coexistence of multiple attractors attributes to the complex outbreak patterns. We first determine the conditions on parameters for the existence of an isolated center, then properly perturb the model to generate Hopf bifurcation and obtain limit cycles around the center. We further analytically prove that the maximum number of the coexisting limit cycles is three, and provide a corresponding set of parameters for the existence of the three limit cycles. Simulation results demonstrate the case with the maximum coexisting attractors, which contains one stable disease free equilibrium and two stable endemic periodic solutions separated by one unstable periodic solution. Therefore, different disease outcomes can be predicted by a single nonlinear deterministic model based on different initial data.     

考虑消费动机和动态竞争的电影日需求预测模型

提出并验证考虑消费动机和动态竞争的电影日需求预测模型。考虑非粉丝及粉丝型的消费动机,构建电影消费两阶段过程模型;融合该模型和Bass模型,考虑竞争导致市场潜量的动态性,考虑映前被关注度、口碑、节假日对票房的影响,提出电影日需求预测模型。利用2016~2017年上映的电影数据验证该模型,并与Bass模型对比分析。结果显示,该模型预测效果优于Bass模型。因考虑竞争导致的动态市场潜量,考虑粉丝型消费者由续集效应及改编效应导致的动态市场潜量提升,该模型能显著提高预测准确度。利用映前被关注度和电影口碑数据,该模型能实现映前及上映早期的预测。该模型可推广至存在消费动机不同、市场动态竞争的其它短生命周期体验品的需求预测,是对Bass模型的改进。     

第三方数据平台精准营销收费模式研究

第三方数据平台通过大数据分析技术为商家提供精准营销服务,本文研究了两个竞争商家通过同一个数据平台进行精准营销时,平台收费模式(费率佣金与按销量收费)对商家竞争以及平台与商家利润的影响。研究发现:1)费率佣金模式的绩效依赖于费率参数,在精准度高的情况下,它不能最大化平台与商家的利润。2)与费率佣金相比,按销量收费模式显著提高了商家的利润,并且平台与商家的利润都随费用参数的增加而增加。3)从收费模式选择的角度,精准度越高,按销量收费模式的优势越明显;费率佣金模式适用于垄断情况,而按销量收费模式更适用于竞争情况。4)费率佣金与按销量收费的结合可以实现平台与商家的共赢。研究结论为大数据驱动下的精准营销收费模式选择,以及“大数据平台”的盈利模式创新提供了理论参考。