Modelling the performance of isoniazid preventive therapy for reducing tuberculosis in HIV endemic settings: the effects of network structure

Individuals living with HIV experience a much higher risk of progression from latent M. tuberculosis infection to active tuberculosis (TB) disease relative to individuals with intact immune systems. A several-month daily course of a single drug during latent infection (i.e. isoniazid preventive therapy (IPT)) has proved in clinical trials to substantially reduce an HIV-infected individual''s risk of TB disease. As a result of these findings and ongoing studies, the World Health Organization has produced strong guidelines for implementing IPT on a community-wide scale for individuals with HIV at risk of TB disease. To date, there has been limited use of IPT at a community-wide level. In this paper, we present a new co-network model for HIV and TB co-epidemics to address questions about how the population-level impact of community-wide IPT may differ from the individual-level impact of IPT offered to selected individuals. In particular, we examine how the effect of clustering of contacts within high-TB incidence communities may affect the rates of re-infection with TB and how this clustering modifies the expected population-level effects of IPT. We find that populations with clustering of respiratory contacts experience aggregation of TB cases and high numbers of re-infection events. While, encouragingly, the overall population-level effects of community-wide IPT appear to be sustained regardless of network structure, we find that in populations where these contacts are highly clustered, there is dramatic heterogeneity in the impact of IPT: in some sub-regions of these populations, TB is nearly eliminated, while in others, repeated re-infection almost completely undermines the effect of IPT. Our findings imply that as IPT programmes are brought to scale, we should expect local heterogeneity of effectiveness as a result of the complex patterns of disease transmission within communities.     

Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis

HIV has fuelled increasing tuberculosis (TB) incidence in sub-Saharan Africa. Better control of TB in this region may be achieved directly through TB programme improvements and indirectly through expanded use of antiretroviral therapy (ART) among those with HIV. We used a mathematical model of TB and HIV in South Africa to examine the potential epidemiological impact in scenarios involving improvements in three dimensions of TB programmes: coverage, diagnosis and treatment effectiveness, as well as expanded ART use through broadened eligibility. We projected the effect of alternative scenarios on TB prevalence, incidence and TB-related mortality over 20 years. Of the three dimensions of TB programme improvement, expanding coverage would produce the greatest reduction in TB burden. Compared with current performance, combined TB programme improvements were projected to decrease TB incidence by 30% over 5 years and 46% over 20 years, and decrease TB-related mortality by 45% over 5 years and 69% over 20 years. Expanded ART eligibility was projected to decrease TB incidence by 22% over 5 years and 45% over 20 years, and TB-related mortality by 22% over 5 years and 50% over 20 years. We found that over a 20-year horizon, TB-specific and HIV-specific programme changes contribute equally to incidence reductions, whereas the TB-specific changes produce a majority of the mortality benefits. An aggressive expansion of ART alongside traditional TB-specific control measures has the potential to greatly reduce TB burden, with the different elements of a combined approach having a synergistic effect in reducing long-term TB incidence and mortality.     

Noise, nonlinearity and seasonality: the epidemics of whooping cough revisited

Understanding the mechanisms that generate oscillations in the incidence of childhood infectious diseases has preoccupied epidemiologists and population ecologists for nearly two centuries. This body of work has generated simple yet powerful explanations for the epidemics of measles and chickenpox, while the dynamics of other infectious diseases, such as whooping cough, have proved more challenging to decipher. A number of authors have, in recent years, proposed that the noisy and somewhat irregular epidemics of whooping cough may arise due to stochasticity and its interaction with nonlinearity in transmission and seasonal variation in contact rates. The reason underlying the susceptibility of whooping cough dynamics to noise and the precise nature of its transient dynamics remain poorly understood. Here we use household data on the incubation period in order to parametrize more realistic distributions of the latent and infectious periods. We demonstrate that previously reported phenomena result from transients following the interaction between the stable annual attractor and unstable multiennial solutions.     

Global dynamics of a time delayed SIR model with varying population size

A disease transmission model of susceptible-infective-recovered type with a constant latent period is analysed. The global dynamics of the disease-free equilibrium is investigated. If the basic reproduction number is greater than unity, a unique endemic equilibrium exists. Using Lyapunov functional approach, this endemic equilibrium is globally stable in the feasible region. The disease will persist (and is permanent) at the endemic equilibrium if it is initially present. The effects of loss of immunity on the dynamics of the model are analysed, and the parameters that drive the disease dynamics are obtained. Numerical simulations support our analytical results and illustrate possible behavioural scenarios of the model.     

Disease transmission in territorial populations: the small-world network of Serengeti lions

Territoriality in animal populations creates spatial structure that is thought to naturally buffer disease invasion. Often, however, territorial populations also include highly mobile, non-residential individuals that potentially serve as disease superspreaders. Using long-term data from the Serengeti Lion Project, we characterize the contact network structure of a territorial wildlife population and address the epidemiological impact of nomadic individuals. As expected, pride contacts are dominated by interactions with neighbouring prides and interspersed by encounters with nomads as they wander throughout the ecosystem. Yet the pride–pride network also includes occasional long-range contacts between prides, making it surprisingly small world and vulnerable to epidemics, even without nomads. While nomads increase both the local and global connectivity of the network, their epidemiological impact is marginal, particularly for diseases with short infectious periods like canine distemper virus. Thus, territoriality in Serengeti lions may be less protective and non-residents less important for disease transmission than previously considered.     

复合Logistic模型对SARS区域疫情的动态描述

根据传染病的发生、发展、流行和转归的基本规律,推导出描述疫情发展的复合Logistic方程模型.从模型曲线和模型参数的实际意义出发,以北京地区为例,对SARS流行的特征参数进行计算、分析与数值预报,从而预见性地阐述SARS流行的数量化规律.并通过模型中参数数值的变化,分析政府措施的效用和节假日对疫情的影响.     

The role of heterogeneity in contact timing and duration in network models of influenza spread in schools

Influenza poses a significant health threat to children, and schools may play a critical role in community outbreaks. Mathematical outbreak models require assumptions about contact rates and patterns among students, but the level of temporal granularity required to produce reliable results is unclear. We collected objective contact data from students aged 5–14 at an elementary school and middle school in the state of Utah, USA, and paired those data with a novel, data-based model of influenza transmission in schools. Our simulations produced within-school transmission averages consistent with published estimates. We compared simulated outbreaks over the full resolution dynamic network with simulations on networks with averaged representations of contact timing and duration. For both schools, averaging the timing of contacts over one or two school days caused average outbreak sizes to increase by 1–8%. Averaging both contact timing and pairwise contact durations caused average outbreak sizes to increase by 10% at the middle school and 72% at the elementary school. Averaging contact durations separately across within-class and between-class contacts reduced the increase for the elementary school to 5%. Thus, the effect of ignoring details about contact timing and duration in school contact networks on outbreak size modelling can vary across different schools.     

Mycobacterium bovis shedding patterns from experimentally infected calves and the effect of concurrent infection with bovine viral diarrhoea virus

Concurrent infection of cattle with bovine viral diarrhoea virus (BVDV) and Mycobacterium bovis is considered to be a possible risk factor for onward transmission of bovine tuberculosis (BTB) in infected cattle and is known to compromise diagnostic tests. A comparison is made here of M. bovis shedding (i.e. release) characteristics from 12 calves, six experimentally co-infected with BVDV and six infected with M. bovis alone, using simple models of bacterial replication. These statistical and mathematical models account for the intermittent or episodic nature of shedding, the dynamics of within-host bacterial proliferation and the sampling distribution from a given shedding episode. We show that while there are distinct differences among the shedding patterns of calves given the same infecting dose, there is no statistically significant difference between the two groups of calves. Such differences as there are, can be explained solely in terms of the shedding frequency, but with all calves potentially excreting the same amount of bacteria in a given shedding episode post-infection. The model can be thought of as a process of the bacteria becoming established in a number of discrete foci of colonization, rather than as a more generalized infection of the respiratory tract. In this case, the variability in the shedding patterns of the infected calves can be explained solely by differences in the number of foci established and shedding being from individual foci over time. Should maximum exposure on a particular occasion be a critical consideration for cattle-to-cattle transmission of BTB, cattle that shed only intermittently may still make an important contribution to the spread and persistence of the disease.     

基于BP神经网络模型的Ni-SiC纳米镀层耐磨性能预测研究

采用神经网络技术,构建结构为3×8×1型的BP神经网络模型,并利用该模型对超声电沉积Ni-SiC纳米镀层的耐磨性能进行预测。通过磨损试验测试并研究Ni-SiC纳米镀层的耐磨性能,利用扫描电镜(SEM)、原子力显微镜(AFM)和X射线衍射(XRD)观察不同参数下Ni-SiC纳米镀层的组织结构及成分。结果表明,在BP神经网络模型的隐含层数和神经元数分别为1和8时,该BP神经网络模型的均方根误差最小,其最小值为1.24%。该BP神经网络模型的预测值与实验值相差不大,其最大误差为1.51%。当采用SiC粒子浓度8 g/L、电流密度2 A/dm^2、温度40℃时,SiC粒子均匀分布于Ni-SiC纳米镀层中,且镀层镍晶粒显著细化,其镍晶粒的衍射峰变宽、变矮。     

Epidemiological game-theory dynamics of chickenpox vaccination in the USA and Israel

The general consensus from epidemiological game-theory studies is that vaccination coverage driven by self-interest (Nash vaccination) is generally lower than group-optimal coverage (utilitarian vaccination). However, diseases that become more severe with age, such as chickenpox, pose an exception to this general consensus. An individual choice to be vaccinated against chickenpox has the potential to harm those not vaccinated by increasing the average age at infection and thus the severity of infection as well as those already vaccinated by increasing the probability of breakthrough infection. To investigate the effects of these externalities on the relationship between Nash and utilitarian vaccination coverages for chickenpox, we developed a game-theory epidemic model that we apply to the USA and Israel, which has different vaccination programmes, vaccination and treatment costs, as well as vaccination coverage levels. We find that the increase in chickenpox severity with age can reverse the typical relationship between utilitarian and Nash vaccination coverages in both the USA and Israel. Our model suggests that to obtain herd immunity of chickenpox vaccination, subsidies or external regulation should be used if vaccination costs are high. By contrast, for low vaccination costs, improving awareness of the vaccine and the potential cost of chickenpox infection is crucial.     

Impact of scale on the effectiveness of disease control strategies for epidemics with cryptic infection in a dynamical landscape: an example for a crop disease.

We use a spatially explicit, stochastic model to analyse the effectiveness of different scales of local control strategies in containing the long-term, multi-seasonal spread of a crop disease through a dynamically changing population of susceptible crops in which there is cryptic infection. The model distinguishes between susceptible, infested and symptomatic fields. It is motivated by rhizomania disease on sugar beet in the UK as an exemplar of a spatially structured and partially asymptomatic epidemic. Our results show the importance of matching the scales of local control strategies to prevent intensification and regional spread of disease with the inherent temporal and spatial scales of an epidemic. A simple field-scale containment strategy, whereby the susceptible crop is no longer grown on fields showing symptoms, fails for this system with cryptic infection because the locally applied control lags behind the epidemic. A farm-scale strategy, whereby growers respond to the disease status of neighbouring farms by transferring their quota for sugar beet to farmers in regions of reduced risk, succeeds. We conclude that a soil-borne pathogen such as rhizomania could be managed by movement of susceptible crops in the landscape using a strategy that matches the temporal and spatial scales of the epidemic and which take account of risk aversion among growers. We show some parallels and differences in effectiveness between a 'culling' strategy involving crop removal around emerging foci and the local deployment of partially resistant varieties that reduce amplification and transmission of inoculum. Some relationships between the control of plant and livestock diseases are briefly discussed.     

On the model building for transmission line cables: a Bayesian approach

This work is aimed at building models to predict the bending vibrations of stranded cables used in high-voltage transmission lines. The present approach encompasses model calibration, validation and selection based on a statistical framework. Model calibration is tackled using a Bayesian framework and the Delayed Rejection Adaptive Metropolis (DRAM) sampling algorithm is employed to explore the posterior probability of the unknown model parameters. Two model classes are proposed to predict the bending vibrations of a typical high-voltage stranded cable. Both model classes account for the aerodynamic damping with the surrounding medium and the bending stiffness of the cable. The difference between the two relies on the damping model chosen to quantify the energy dissipation due to friction among the constituent wires of the cable. Model ranking is rigorously quantified by means of a Bayesian model class selection approach, in which both the data-fitting capability and complexity of each model class are simultaneously taken into account. Experimental tests are performed on a laboratory span with a typical high-voltage stranded cable. The measured frequency response functions are the observable quantities employed in the Bayesian model updating for the two model classes proposed. Both model classes provide comparable and accurate predictions for the cable’s frequency response functions within the range [5, 25] Hz, with the fractional derivative-based model class providing the most accurate predictions. Nonetheless, both model classes failed to accurately reproduce the measured cable’s dynamic response within the frequency range [25, 30] Hz.     

A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues

Cancers are rarely caused by single mutations, but often develop as a result of the combined effects of multiple mutations. For most cells, the number of possible cell divisions is limited because of various biological constraints, such as progressive telomere shortening, cell senescence cascades or a hierarchically organized tissue structure. Thus, the risk of accumulating cells carrying multiple mutations is low. Nonetheless, many diseases are based on the accumulation of such multiple mutations. We model a general, hierarchically organized tissue by a multi-compartment approach, allowing any number of mutations within a cell. We derive closed solutions for the deterministic clonal dynamics and the reproductive capacity of single clones. Our results hold for the average dynamics in a hierarchical tissue characterized by an arbitrary combination of proliferation parameters. We show that hierarchically organized tissues strongly suppress cells carrying multiple mutations and derive closed solutions for the expected size and diversity of clonal populations founded by a single mutant within the hierarchy. We discuss the example of childhood acute lymphoblastic leukaemia in detail and find good agreement between our predicted results and recently observed clonal diversities in patients. This result can contribute to the explanation of very diverse mutation profiles observed by whole genome sequencing of many different cancers.     

A mathematical model of a crystal oscillator and clock in the form of an augmented system of state equations

An analysis of a mathematical model of a crystal oscillator and clock and disturbances in the form of an augmented system of state equations is performed. By means of such a model, it is possible to synthesize an optimal frequency-time stabilization system for the GLONASS/GPS synchronizing reference receiver. __________ Translated from Izmeritel’naya Tekhnika, No. 4, pp. 35–38, April, 2007.     

Networks of influence and infection: parental choices and childhood disease

Clusters of unvaccinated individuals are at risk of outbreaks of infection. When an individual''s decision to choose vaccination is influenced by the choices of his social group, such clusters can readily arise. However, when the interactions that influence decision-making and those that permit the transmission of infection are different—for instance, when parents make vaccination decisions on behalf of their children—it is unclear how large the impact of this social influence will be. Here we use a modelling approach to represent social influence within a network of parents and the transmission of infection through a network of children. We show that the effect of social influence depends on the amount of overlap between the two different networks; large overlap means that clusters of parents who choose not to vaccinate are likely to have interacting children, generating clusters of unvaccinated children. Spatially local connections can further increase the impact of social influence. Outbreaks are most likely when parents who do not vaccinate have children who interact.     

Stochasticity in staged models of epidemics: quantifying the dynamics of whooping cough

Although many stochastic models can accurately capture the qualitative epidemic patterns of many childhood diseases, there is still considerable discussion concerning the basic mechanisms generating these patterns; much of this stems from the use of deterministic models to try to understand stochastic simulations. We argue that a systematic method of analysing models of the spread of childhood diseases is required in order to consistently separate out the effects of demographic stochasticity, external forcing and modelling choices. Such a technique is provided by formulating the models as master equations and using the van Kampen system-size expansion to provide analytical expressions for quantities of interest. We apply this method to the susceptible–exposed–infected–recovered (SEIR) model with distributed exposed and infectious periods and calculate the form that stochastic oscillations take on in terms of the model parameters. With the use of a suitable approximation, we apply the formalism to analyse a model of whooping cough which includes seasonal forcing. This allows us to more accurately interpret the results of simulations and to make a more quantitative assessment of the predictions of the model. We show that the observed dynamics are a result of a macroscopic limit cycle induced by the external forcing and resonant stochastic oscillations about this cycle.     

Quantum effects in the transient dynamics of a many mode Jaynes-Cummings model

Abstract

Phenomenology and mechanisms of energy exchange, due to induced atomic processes of absorption and emission, are investigated in the evolution of a two-mode Jaynes-Cummings model. One field mode is initially in a highly coherent populated state and the other one is initially empty. The field mode exchanges energy with the atom by two mechanisms, related to very different atomic dynamics, which operate in complementary phases of the system evolution. One mechanism determines the energy exchanges which involve only the populated mode and the atom. The other is responsible for mode-mode photon exchanges and becomes relevant when the first mechanism is quenched. Thus there is no competition between the atomic emission in the empty mode and processes involving the atom and the highly populated mode. Quantum features related to entanglement of atom and field states are discussed. Cooperative effects between the two field modes and their incompatibility with the predictions of neo-classical theory are evidenced.     

一个积分-微分方程模型解的存在唯一性

积分-微分方程组（1)是对一种流行病（肺结核)作理论研究过程中提出来的数学模型。本文得到了该系统之解存在唯一的充要条件．     

船舶发电机组转速神经网络模型参考自适应控制研究

将基于神经网络的模型参考自适应控制（NNMRAC）作为控制策略用于研究船舶发电机组的时变与非线性转速控制,以提高控制质量。研究中建立了船舶发电机组二阶传递函数模型,模型参考自适应控制的神经网络辨识器与控制器均采用多层前馈拓扑结构,网络训练采用量化共轭梯度反向传播优化学习算法。学习完成的神经网络模型参考自适应控制器与PID控制器并行作用于船舶发电机组,仿真数据表明船舶发电机组转速控制系统的调速快速性得到了提高、灵敏度得到了改善。