一类传染病模型的加权伪几乎自守解（英文）

利用锥上不动点定理,研究了传染病模型中一类非线性时滞积分方程的加权伪几乎自守行为.作为应用,给出了一些例子来验证主要的结论.     

时滞传染病模型的指数稳定性

利用分析技巧研究了一类SEIRS传染病模型的动力学行为.结论表明如果再生数小于1,则带变时滞的传染病模型的无病平衡点是全局指数渐近稳定的,如果再生数大于1,得到传染病平衡点局部指数稳定的充分条件,同时给出了例子说明结论的有效性.     

具有非线性种内制约关系和分布时滞竞争模型的稳定性

构造并研究了一类具有分布时滞和非线性种内制约关系的竞争模型.得到了这类模型的边界平衡点和共存平衡点全局渐近稳定的条件,以及分布时滞、非线性种内制约关系对模型的影响.     

一类具有潜伏时滞和非线性疾病发生率的SEIRS传染病模型

本文提出一类具有潜伏时滞和非线性疾病发生率的SEIRS传染病模型,通过分析对应的特征方程,运用时滞微分方程的稳定性理论得出:当基本再生数R_01时无病平衡点处的局部渐近稳定性,R_0 1时地方病平衡点处的局部渐近稳定性.通过构造Lyapunov泛函,运用LaSalle's不变集原理得到:当基本再生数R_0≤1时无病平衡点处的全局渐近稳定性;通过比较方法得到R_01时系统的一致持久性     

具有脉冲接种的时滞SEIR传染病模型

研究了一类具有饱和发生率及脉冲接种的时滞SEIR传染病模型,得到了基本再生数,运用脉冲微分方程的比较原理证明了无病周期解的全局吸引性,获得了疾病持久性的充分条件.通过数值模拟验证了结论的准确性.     

一类具有非单调感染率的时滞传染病模型的全局稳定性(英文)

通过构造Lyapunov函数研究了一类具有非单调感染率的时滞传染病模型,并证明了该模型的无病平衡点和地方性平衡点的全局稳定性.     

具有垂直传染和时滞的肺结核传染病模型

建立了一类含时滞具有垂直传染的肺结核传染病模型,得到了系统的基本再生数R_0.利用平衡点处的特征方程讨论平衡点的局部渐近稳定性;通过构造Lyapunov函数讨论地方病平衡点的全局渐近稳定性;运用比较定理和分析的方法得到无病平衡点的全局渐近稳定性和地方病平衡点的持久性;最后利用数值模拟分析了时滞在模型中的影响.     

一类具有潜伏期的虫媒传染病模型的动力学分析

研究一类具有潜伏期的时滞虫媒传染病模型,确定了疾病是否流行的阈值.利用特征值理论分析了无病平衡点和地方病平衡点的稳定性,以时滞为参数,得到了系统在地方病平衡点产生Hopf分支的条件.数值模拟验证了理论研究的有效性.     

一类SI传染病模型的平衡点稳定性及行波解的存在性（英文）

本文考虑了一类SI传染病模型,并引入了扩散和时滞的影响,得到一类捕食型的反应扩散模型.运用线性化方法得到了该系统平衡点的稳定性,由此指出了控制传染病传播的有效措施.然后运用上下解单调迭代的方法证明了行波解的存在性.     

一类带有非线性感染率传染病模型的动力学性质（英文）

主要介绍了一类带有非线性感染率的传染病模型.并且证明了当基本再生数Ro≤1时,无病平衡点是全局稳定的,当基本再生数R_0〉1时,疾病持续.     

具有潜伏期的无免疫型传染病动力学模型的分析

研究了一类具有潜伏期的无免疫型传染病动力学模型,用摄动理论讨论分析了相应的非线性系统,得到了不同群体生存变化的渐近表达式,从而揭示了各种作用对不同群体生存影响的规律.本文的研究为解决一些类型的非线性模型提供了一种有效的方法.     

Study of the effect of vaccination on periodic structures of measles epidemics in Japan

The purpose of this paper is to investigate the effect of vaccination on periodic structures of measles epidemics in Japan. We carried out spectral analysis for time series data of measles notifications collected in Japan. It was confirmed that the interepidemic period, which corresponds to the interval between major epidemics of measles, increases as the vaccination ratio increases. This result was supported by a theory based on a mathematical model for epidemics of infectious diseases. It was suggested that the interepidemic period is useful to estimate the effect of vaccination on measles incidences quantitatively.     

Integral equation models for endemic infectious diseases

Summary Endemic infectious diseases for which infection confers permanent immunity are described by a system of nonlinear Volterra integral equations of convolution type. These constant-parameter models include vital dynamics (births and deaths), immunization and distributed infectious period. The models are shown to be well posed, the threshold criteria are determined and the asymptotic behavior is analysed. It is concluded that distributed delays do not change the thresholds and the asymptotic behaviors of the models.This work was partially supported by NIH Grant AI 13233.     

Emerging and Reemerging Infectious Diseases: Biocomplexity as an Interdisciplinary Paradigm

Understanding factors responsible for reemergence of diseases believed to have been controlled and outbreaks of previously unknown infectious diseases is one of the most difficult scientific problems facing society today. Significant knowledge gaps exist for even the most studied emerging infectious diseases. Coupled with failures in the response to the resurgence of infectious diseases, this lack of information is embedded in a simplistic view of pathogens and disconnected from a social and ecological context, and assumes a linear response of pathogens to environmental change. In fact, the natural reservoirs and transmission rates of most emerging infectious diseases primarily are affected by environmental factors, such as seasonality or meteorological events, typically producing nonlinear responses that are inherently unpredictable. A more realistic view of emerging infectious diseases requires a holistic perspective that incorporates social as well as physical, chemical, and biological dimensions of our planet’s systems. The notion of biocomplexity captures this depth and richness, and most importantly, the interactions of human and natural systems. This article provides a brief review and a synthesis of interdisciplinary approaches and insights employing the biocomplexity paradigm and offers a social–ecological approach for addressing and garnering an improved understanding of emerging infectious diseases. Drawing on findings from studies of cholera and other examples of emerging waterborne, zoonotic, and vectorborne diseases, a “blueprint” for the proposed interdisciplinary research framework is offered which integrates biological processes from the molecular level to that of communities and regional systems, incorporating public health infrastructure and climate aspects.     

The correlation between infectivity and incubation period of measles, estimated from households with two cases

The generation time of an infectious disease is the time between infection of a primary case and infection of a secondary case by the primary case. Its distribution plays a key role in understanding the dynamics of infectious diseases in populations, e.g. in estimating the basic reproduction number. Moreover, the generation time and incubation period distributions together characterize the effectiveness of control by isolation and quarantine. In modelling studies, a relation between the two is often not made specific, but a correlation is biologically plausible. However, it is difficult to establish such correlation, because of the unobservable nature of infection events. We have quantified a joint distribution of generation time and incubation period by a novel estimation method for household data with two susceptible individuals, consisting of time intervals between disease onsets of two measles cases. We used two such datasets, and a separate incubation period dataset. Results indicate that the mean incubation period and the generation time of measles are positively correlated, and that both lie in the range of 11-12 days, suggesting that infectiousness of measles cases increases significantly around the time of symptom onset. The correlation between times from infection to secondary transmission and to symptom onset could critically affect the predicted effectiveness of isolation and quarantine.     

气候变化对传染病爆发流行的影响研究进展

全球气候变化已影响到传染病发生、传播与变化的各个环节,从病原体及其携带者、传播途径和人体自身抵抗力等方面直接或间接影响传染病的发病趋势,从而对人类健康造成了巨大的威胁。所以加强对气候变化与传染病间关系、预测预报研究,对进一步认识、预防和控制传染病的爆发流行具有重要意义。本文首先阐述了全球气候变化对生物物种的地理分布和人类健康的影响,气候变化改变了生物物种的地理分布范围,增加了某些物种的潜在分布区域,并造成生物物侯期的改变;同时,极端气候事件成为导致种群数量波动的一个重要驱动力。气候变化对人类健康有直接和间接影响,它使得传染病发病率增加、传染病分布范围扩大、人群对疾病易感性增强。文章重点评述了气候变化对疟疾、登革热、霍乱、流行性乙型脑炎、流感、SARS、肠道传染病、鼠疫、血吸虫病等常见传染病流行机制和传播过程的影响研究进展。评述了传染病和气象因子关系分析中常用的定性和定量分析方法,传统的研究多以定性分析为主,方法较单一;目前,利用流行病学资料与同期的气象因子进行单因素相关分析、多元回归分析是常用的研究方法;主成分回归分析、逐步判别分析、灰色关联分析法、RS和GIS等方法近年来逐渐得到应用;数学建模、实验室生物学仿真实验方法是今后需强化的方向。提出了该研究领域国内外研究普遍存在和亟待解决的问题,针对目前的研究现状和存在的问题,提出了未来的研究重点和发展方向。     

IgG and IgM levels in dairy cows during the periparturient period

In dairy cows, the incidence of infectious diseases during the periparturient period is high. The most common diseases ante partum (a.p.) and post partum (p.p.) are mastitis and puerperal toxicaemia, puerperal septicaemia, and chronic endometritis, respectively. Studies suggest that this is related to an immunosuppressed status during this period.Therefore, the aim of this study was to determine the periparturient immune status characterized by concentrations of IgG and IgM in peripheral blood and colostrum samples of dairy cows and to assess in detail whether variations in immunoglobulin levels may be related to age and status of productivity. In addition, a possible correlation between the course of immunoglobulin levels and lymphocyte concentrations was assessed.Eighteen clinically healthy German Holstein and Red Holstein dams were selected for this study and sampled regularly between the 8^th week a.p. and the 4^th week p.p. IgG and IgM levels were determined using two novel competitive ELISAs.Results demonstrated a dramatic decrease of serum IgG and IgM levels beginning at the 8^th week and 4^th week a.p., respectively, both reaching trough at parturition. The IgG level recovered by the 4^th week p.p., while IgM concentrations remained low. The extent of IgG reduction seemed to be dependent on the initial IgG concentration when the cow was dried-off (8^th week a.p.). In contrast to IgM, the degree of IgG reduction correlated significantly with the IgG concentrations in the colostrum. Furthermore, a cross-correlation between the IgG levels and the lymphocyte counts was detectable (P < 0.01).In conclusion, the antepartal decline of blood IgG and IgM levels as well as the low periparturient IgG levels could reflect a “physiological phenomenon” of dairy cattle. If the phenomenon is associated with an unstable immune system, it must be assessed in future studies. Nonetheless, a sensitive immune system could explain the high incidence for infectious diseases during this period.     

The real place of infectious pathology in overall population morbidity

The statistical decrease of the proportion of infections in the structure of morbidity of the population reflects the existing classification of diseases when only acute diseases are classified with the group "infectious and parasitic diseases". The proportion of diseases caused by infective agents remains constantly high. According to WHO data, such diseases make up one-third of all diseases in the world. In Moscow the proportion of infectious diseases in all diseases registered among the inhabitants of this big city fluctuated within 36.1% and 49.7% during the period of 1926-1997.     

具潜伏期的无免疫型传染病动力学的微分模型

对具潜伏期的无免疫型传染病进行讨论,给出一个常微分模型和一个偏微分模型．     

From Pasteur to genomics: progress and challenges in infectious diseases

Over the past decade, microbiology and infectious disease research have undergone the most profound revolution since the times of Pasteur. Genomic sequencing has revealed the much-awaited blueprint of most pathogens. Screening blood for the nucleic acids of infectious agents has blunted the spread of pathogens by transfusion, the field of antiviral therapeutics has exploded and technologies for the development of novel and safer vaccines have become available. The quantum jump in our ability to detect, prevent and treat infectious diseases resulting from improved technologies and genomics was moderated during this period by the greatest emergence of new infectious agents ever recorded and a worrisome increase in resistance to existing therapies. Dozens of new infectious diseases are expected to emerge in the coming decades. Controlling these diseases will require a better understanding of the worldwide threat and economic burden of infectious diseases and a global agenda.