基于网络媒体信息的传染病传播模型及其仿真研究

当一种突发传染病开始流行时,政府、媒体会以各种形式告知民众,有防范意识的民众将采取一定的防范措施来降低感染率.考虑面对一种突发传染病,将易感群体划分为具有防范意识和不具有防范意识两种群体,利用生命周期理论,分析网络媒体信息报道对传染病传播的影响,以此为依据建立一种改进的传染病传播模型(MSI).利用网络大数据得到对传染病有防范意识群体的观测值信息,利用神经网络技术对模型MSI的参数进行反演.然后对模型MSI数值仿真得到传染病传播过程,提出了相应的控制措施.     

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.     

公共场所突发事件情境下受灾人群间信息的传播与扩散研究

针对公共场所突发事件情境下受灾人群间信息传播与扩散的特征,定义一种受灾人群间信息传播与扩散的微分过程.根据公共场所突发事件情境下信息的多元性,将信息分为消极信息和积极信息,基于Gilpin-Ayala扩散模型,建立一种基于公共场所突发事件情境下的受灾人群间信息传播与扩散模型,并对模型的动态过程进行分析,提出并证明了最佳安全疏散汇集点定理.利用定理的结论,分析突发信息传播扩散可能出现的情况,进一步分析信息传播与扩散对受灾人群的影响.最后通过算例计算分析,验证了理论的正确性和有效性,并根据计算结果给出了几点政策建议.     

突发事件中不实信息的竞争扩散研究

基于Gilpin-Ayala扩散模型,建立了突发事件中不实信的竞争扩散与传播模型,并对模型的动态过程进行深入分析.针对突发事件发生后存在多种信息的竞争扩散的问题,模型能给予很好的解释.最后,就相关问题和分析结果,为应急管理者在突发事件中如何引导舆论提供政策建议.     

具有媒体效应和时滞的反应扩散传染病模型的控制与预测

针对媒体效应的传染病建立相应的反应扩散模型,研究平衡点的稳定性、Hopf分岔以及重要参数如时滞、传染率和媒体效应等对模型Turing结构的影响.最后,给出精确Turing失稳的参数条件,并给出相应的数值模拟,得到条状和点状共存的斑图.理论分析与数值模拟揭示了空间动力学复杂性机理,为控制疾病的传播提供了有力理论依据.     

我国通讯产品扩散的模型分析

利用Bass创新扩散模型描述我国无线寻呼和移动电话的扩散过程.通过对无线寻呼和移动电话的历史数据进行模型参数的估计,建立无线寻呼和移动电话的采用者扩散模型,分析无线寻呼被市场淘汰的原因和移动电话的市场前景.最后根据模型得出的结果对模型进行了讨论     

一类具有扩散项的流行性传染病模型中的行波解

讨论了一类具有扩散项的流行性传染病模型中的行波解的存在性.首先,将对该模型所对应的反应扩散系统的行波解的讨论转化为对二阶常微分系统的上下解的讨论;然后,通过上下解方法建立了这个具有扩散项的传染病模型中行波解的存在性条件,并进一步讨论了扩散因素对行波解的波速的影响,得到被感染人群的流动对病毒的传播有一定的影响.     

环境制约条件下含两菌株寄生虫的传染模型

研究了环境制约条件下含两菌株寄生虫的传染模型,结合流感病毒的传播规律,考虑同一亚型不同毒株之间的传染病模型.讨论了模型各个平衡点的存在条件,局部渐近稳定的条件,并对模型进行了数值模拟,很好的验证了模型的相关性质和特点.     

具有水平传播和环境传播的反应扩散传染病模型研究

该文提出一类具有水平传播和环境传播的反应扩散传染病模型,讨论模型的适定性,包括解的全局存在性和一致有界性.进一步,通过下一代算子的谱半径定义给出基本再生数R0的精确表达式,并利用单调动力系统理论和一致持续性理论研究模型的阈值动力学.     

一类潜伏期有传染性的传染病模型动力学分析

建立了一类潜伏期具备传染性的传染病传播模型,根据疾病传播规律求解了疾病消失和持续生存的阈值——基本再生数.对系统的稳定性进行了讨论,得到了系统稳定性条件.最后,以COVID-19为例,解释了各种举措在疾病控制中的作用,并对疫情传播扩散做了探讨和预测.     

Efficient Data Augmentation for Fitting Stochastic Epidemic Models to Prevalence Data

Stochastic epidemic models describe the dynamics of an epidemic as a disease spreads through a population. Typically, only a fraction of cases are observed at a set of discrete times. The absence of complete information about the time evolution of an epidemic gives rise to a complicated latent variable problem in which the state space size of the epidemic grows large as the population size increases. This makes analytically integrating over the missing data infeasible for populations of even moderate size. We present a data augmentation Markov chain Monte Carlo (MCMC) framework for Bayesian estimation of stochastic epidemic model parameters, in which measurements are augmented with subject-level disease histories. In our MCMC algorithm, we propose each new subject-level path, conditional on the data, using a time-inhomogenous continuous-time Markov process with rates determined by the infection histories of other individuals. The method is general, and may be applied to a broad class of epidemic models with only minimal modifications to the model dynamics and/or emission distribution. We present our algorithm in the context of multiple stochastic epidemic models in which the data are binomially sampled prevalence counts, and apply our method to data from an outbreak of influenza in a British boarding school. Supplementary material for this article is available online.     

SIR类型新型冠状病毒肺炎多阶段最优控制模型

新型冠状病毒肺炎(COVID-19)疫情在全球范围传播,给人们的健康带来了严重的威胁。面对疫情发展预期数据,我们需要在有限医疗资源的情况下确定疫情传播参数,以指导主要防疫措施的实施力度。本文采用SIR类型的模型描述新冠肺炎疫情发展,并建立多阶段最优控制模型确定疫情传播参数。为了高效确定参数取值,我们建立多项式时间可计算的半定规划近似模型。基于世界卫生组织发布的数据,我们求解近似模型,得到描述给定时段内美国新冠肺炎疫情发展态势的疫情传播参数,并分析疫情防控策略。     

SARS流行病传染动力学模型

建立了 SARS流行病的数学模型 ,根据部分国家和地区的 SARS疫情数据 ,计算出其模型参数 ,给出了各地 SARS疫情与模拟结果的比较图 ,模拟结果与实际疫情十分吻合 .分析了 SARS流行特征 ,并对疫情发展进行了预测 .     

甲流病毒传播的年龄结构模型的稳定性

研究甲型H1N1流感病毒的传播规律,建立年龄结构具有接种措施的SEIR流行病模型,给出了疾病流行的阈值并证明了地方病平衡点的稳定性问题.最后根据一些实际数据,进行数值模拟进而对模型的合理性加以完善,借助模型预测下一阶段甲流爆发的可能性并提出相关应对措施.     

基于Kolmogorov前向方程评估甲型H1N1流感疫情的动态变化北大核心CSCD

基于个体水平的传染病模型可以揭示随机性在传染病疫情防控中的重要作用.研究此类模型的普遍方法是通过事件驱动的、大量重复的随机模拟来确定预测变量的范围.而基于Kolmogorov前向方程(KFE)研究个体水平的传染病模型,不仅不需要大量的重复模拟来确定预测变量的范围,而且可以同时考虑每种状态发生的概率.因此,基于2009年西安市第八医院甲型H1N1流感数据,建立了基于社交网络的个体决策心理模型,以确定行为改变率;进一步地,为得到传染病传播过程中各状态的概率分布,基于改进的个体SIR模型,通过Markov过程推导出KFE.结果表明:通过数值求解KFE可以得到整个爆发过程中每种状态发生的概率分布、最严重的时间段及相应的概率,从而能更快、更准确地了解甲型H1N1疫情的传播过程,因此有助于高效地进行甲型H1N1疫情防控.     

COVID-19 Epidemic Prediction Based on Deep Learning

In this paper, a multi-layer gated recurrent unit neural network (multi-head GRU) model is proposed to predict the confirmed cases of the new crown epidemic (COVID-19). We extract the time series relationship in the data, and the rolling prediction method is adopted to ensure the simple structure of the model and achieve higher precision and interpretability. The prediction results of this model are compared with the LSTM model, the Transformer model and the infectious disease model (SIR). The results show that the proposed model has higher prediction accuracy. The mean absolute error (MAE) of epidemic prediction in most countries (the United States, Brazil, India, the United Kingdom and Russia) is respectively 197.52, 68.02, 200.67, 24.78 and 123.50, which is much smaller than the prediction error of the SIR model, LSTM model and Transformer model. For the spread of the COVID-19 epidemic, traditional infectious disease models and machine learning models cannot achieve more accurate predictions. In this paper, we use a GRU model to predict the real-time spread of COVID-19, which has fewer parameters and reduces the risk of overfitting to train faster. Meanwhile, it can make up for the shortcoming of the transformer model to capture local features.     

Modeling pulse infectious events irrupting into a controlled context: A SIS disease with almost periodic parameters

A new epidemic model of seasonal/cyclical pulse contagions of an infectious disease is introduced: a population with a controlled infectious disease is perturbed by a sequence of pulse infectious events arising from the specific features of the population’s behavior. The purpose of this article is to obtain an epidemic threshold which allows us to decide how a sequence of epidemic events could destabilize the previous controlled scenario and how a new endemic equilibrium appears. A threshold is obtained when supposing a set of almost periodic properties in the model.     

Assessing the effects of homosexuals and bisexuals on the intrinsic dynamics of HIV/AIDS in heterosexual settings

A deterministic compartmental sex-structured HIV/AIDS model for assessing the effects of homosexuals and bisexuals on the intrinsic dynamics of the disease in heterosexual settings in which homosexuality and bisexuality issues have remained taboo is presented. The epidemic threshold and equilibria for the model are determined and stabilities are investigated. Comprehensive qualitative analysis of the model including invariance of solutions and permanence are carried out. The epidemic threshold known as the basic reproductive number suggests that heterosexuality, homosexuality, and bisexuality influence the growth of the epidemic in HIV/AIDS affected populations and the partial reproductive number (homosexuality induced or heterosexuality and bisexuality induced) with the larger value influences the overall dynamics of the epidemic in a setting. Numerical simulations of the model show that as long as one of the partial reproductive numbers is greater than unity, the disease will exist in the population. We conclude from the study that homosexuality and bisexuality enlarge the epidemic in a heterosexual setting. The theoretical study highlights the need to carry out substantial research to map homosexuals and bisexuals as it has remained unclear as to what extent this group has contributed to the epidemic in heterosexual settings especially in southern Africa, which has remained the epidemiological locus of the epidemic.     

The analysis and application of an HBV model

A mathematical model is formulated to describe the spread of hepatitis B. The stability of equilibria and persistence of disease are analyzed. The results shows that the dynamics of the model is completely determined by the basic reproductive number ρ₀. If ρ₀ < 1, the disease-free equilibrium is globally stable. When ρ₀ > 1, the disease-free equilibrium is unstable and the disease is uniformly persistent. Furthermore, under certain conditions, it is proved that the endemic equilibrium is globally attractive. Numerical simulations are conducted to demonstrate our theoretical results. The model is applied to HBV transmission in China. The parameter values of the model are estimated based on available HBV epidemic data in China. The simulation results matches the HBV epidemic data in China approximately.