The structural identifiability of the susceptible infected recovered model with seasonal forcing

In this paper, it is shown that the SIR epidemic model, with the force of infection subject to seasonal variation, and a proportion of either the prevalence or the incidence measured, is unidentifiable unless certain key system parameters are known, or measurable. This means that an uncountable number of different parameter vectors can, theoretically, give rise to the same idealised output data. Any subsequent parameter estimation from real data must be viewed with little confidence as a result. The approach adopted for the structural identifiability analysis utilises the existence of an infinitely differentiable transformation that connects the state trajectories corresponding to parameter vectors that give rise to identical output data. When this approach proves computationally intractable, it is possible to use the converse idea that the existence of a coordinate transformation between states for particular parameter vectors implies indistinguishability between these vectors from the corresponding model outputs.     

Periodicity in an epidemic model with a generalized non-linear incidence

We develop and analyze a simple SIV epidemic model including susceptible, infected and perfectly vaccinated classes, with a generalized non-linear incidence rate subject only to a few general conditions. These conditions are satisfied by many models appearing in the literature. The detailed dynamics analysis of the model, using the Poincaré index theory, shows that non-linearity of the incidence rate leads to vital dynamics, such as bistability and periodicity, without seasonal forcing or being cyclic. Furthermore, it is shown that the basic reproductive number is independent of the functional form of the non-linear incidence rate. Under certain, well-defined conditions, the model undergoes a Hopf bifurcation. Using the normal form of the model, the first Lyapunov coefficient is computed to determine the various types of Hopf bifurcation the model undergoes. These general results are applied to two examples: unbounded and saturated contact rates; in both cases, forward or backward Hopf bifurcations occur for two distinct values of the contact parameter. It is also shown that the model may undergo a subcritical Hopf bifurcation leading to the appearance of two concentric limit cycles. The results are illustrated by numerical simulations with realistic model parameters estimated for some infectious diseases of childhood.     

Stochastic model of an influenza epidemic with drug resistance

A continuous-time Markov chain (CTMC) model is formulated for an influenza epidemic with drug resistance. This stochastic model is based on an influenza epidemic model, expressed in terms of a system of ordinary differential equations (ODE), developed by Stilianakis, N.I., Perelson, A.S., Hayden, F.G., [1998. Emergence of drug resistance during an influenza epidemic: insights from a mathematical model. J. Inf. Dis. 177, 863-873]. Three different treatments-chemoprophylaxis, treatment after exposure but before symptoms, and treatment after symptoms appear, are considered. The basic reproduction number, R(0), is calculated for the deterministic-model under different treatment strategies. It is shown that chemoprophylaxis always reduces the basic reproduction number. In addition, numerical simulations illustrate that the basic reproduction number is generally reduced with realistic treatment rates. Comparisons are made among the different models and the different treatment strategies with respect to the number of infected individuals during an outbreak. The final size distribution is computed for the CTMC model and, in some cases, it is shown to have a bimodal distribution corresponding to two situations: when there is no outbreak and when an outbreak occurs. Given an outbreak occurs, the total number of cases for the CTMC model is in good agreement with the ODE model. The greatest number of drug resistant cases occurs if treatment is delayed or if only symptomatic individuals are treated.     

Chaotic behaviour of an ocean ecosystem model under seasonal external forcing

A four-component ecosystem model of the oceanic upper mixedlayer (UML) forced by the annual cycle of UML depth, solar irradiationand dissolved inorganic nitrogen (DIN) entrainment from theseasonal pycnocline is presented. The model solution demonstratesthe following types of temporal variability: a periodical regimewith the frequency of the external forcing, a regime with aperiod of more than 1 year, quasi-periodic, and chaotic motion.The model results suggest that the last three types describingthe interannual variability can occur only at low latitudesin regions of strong upwelling where the DIN concentration inthe seasonal pycnocline is high. However, the range of externalforcing parameters in which such behaviour takes place is sonarrow that it is unlikely to be a common phenomenon in theocean. The quasi-periodic or chaotic variability of the modelecosystem is very sensitive to the initial conditions, and thereforeany exact prediction of model behaviour is impossible. Nevertheless,a prediction of model ecosystem behaviour can be obtained interms of a probability density. The annual cycle of the modelcomponents calculated in this way shows that the dispersionof the trajectories during the winter period is markedly smallerthan during the summer. It implies that the dynamics of themodel ecosystem during the summer period is less predictable.     

An epidemic model in a patchy environment

An epidemic model is proposed to describe the dynamics of disease spread among patches due to population dispersal. We establish a threshold above which the disease is uniformly persistent and below which disease-free equilibrium is locally attractive, and globally attractive when both susceptible and infective individuals in each patch have the same dispersal rate. Two examples are given to illustrate that the population dispersal plays an important role for the disease spread. The first one shows that the population dispersal can intensify the disease spread if the reproduction number for one patch is large, and can reduce the disease spread if the reproduction numbers for all patches are suitable and the population dispersal rate is strong. The second example indicates that a population dispersal results in the spread of the disease in all patches, even though the disease can not spread in each isolated patch.     

A two-dimensional aerodynamic model of freely flying insects

Possible free flights of insects by a single flapping motion were studied. It is well-known that insects utilize vortices generated by flapping, by which they generate larger lift than that evaluated by the ordinary aerodynamic theory. However, the effect of the motion of the center of mass (CM) of the insect on its flight has not been clarified. To clarify the effect, numerical simulation was performed for a simple model considering the coupling between the vertical CM motion and the separation vortices generated by flapping wing. As a result, it is shown that the flapping flight has the following interesting features. First, despite a single flapping motion, the model exhibits two types of flapping flight: a steady flight in which the CM velocity oscillates and a wandering flight in which the CM velocity varies irregularly. These two types of flights are selected by the initial conditions even when all the parameters are the same. Second, at a certain critical parameter value, the steady flight loses its stability and undergoes an abrupt transition to the wandering flight. Interestingly, at this critical value, the steady flight can be regarded as hovering. The possible flights are analyzed in terms of bifurcation, and the bifurcation structure is qualitatively explained based on a simple assumption. These results suggest the significance of the effect of CM motion.     

Phase locking,period doubling bifurcations and chaos in a mathematical model of a periodically driven oscillator: A theory for the entrainment of biological oscillators and the generation of cardiac dysrhythmias

A mathematical model for the perturbation of a biological oscillator by single and periodic impulses is analyzed. In response to a single stimulus the phase of the oscillator is changed. If the new phase following a stimulus is plotted against the old phase the resulting curve is called the phase transition curve or PTC (Pavlidis, 1973). There are two qualitatively different types of phase resetting. Using the terminology of Winfree (1977, 1980), large perturbations give a type 0 PTC (average slope of the PTC equals zero), whereas small perturbations give a type 1 PTC. The effects of periodic inputs can be analyzed by using the PTC to construct the Poincaré or phase advance map. Over a limited range of stimulation frequency and amplitude, the Poincaré map can be reduced to an interval map possessing a single maximum. Over this range there are period doubling bifurcations as well as chaotic dynamics. Numerical and analytical studies of the Poincaré map show that both phase locked and non-phase locked dynamics occur. We propose that cardiac dysrhythmias may arise from desynchronization of two or more spontaneously oscillating regions of the heart. This hypothesis serves to account for the various forms of atrioventricular (AV) block clinically observed. In particular 22 and 42 AV block can arise by period doubling bifurcations, and intermittent or variable AV block may be due to the complex irregular behavior associated with chaotic dynamics.     

Dynamic equilibria in an epidemic model with voluntary vaccinations

The dynamics of an epidemic model with voluntary vaccinations are studied. Individual vaccination decisions are modelled using an economic/game-theoretic approach: agents in the model decide whether to vaccinate or not by weighing the cost and benefit of vaccination and choose the action that maximizes their net benefit. It is shown that, when vaccine efficacy is low, there are parameter values for which multiple steady-state equilibria and periodic equilibria coexist. When multiplicity of steady states is obtained, which one the population reaches in some cases depends entirely on agents' expectations concerning the future course of an epidemic and not on the initial conditions of the model. (?)Comments and suggestions from anonymous referees of the journal are gratefully acknowledged. This paper is dedicated to the loving memory of Lucy Hauser.     

Backward bifurcations and multiple equilibria in epidemic models with structured immunity

Many disease pathogens stimulate immunity in their hosts, which then wanes over time. To better understand the impact of this immunity on epidemiological dynamics, we propose an epidemic model structured according to immunity level that can be applied in many different settings. Under biologically realistic hypotheses, we find that immunity alone never creates a backward bifurcation of the disease-free steady state. This does not rule out the possibility of multiple stable equilibria, but we provide two sufficient conditions for the uniqueness of the endemic equilibrium, and show that these conditions ensure uniqueness in several common special cases. Our results indicate that the within-host dynamics of immunity can, in principle, have important consequences for population-level dynamics, but also suggest that this would require strong non-monotone effects in the immune response to infection. Neutralizing antibody titer data for measles are used to demonstrate the biological application of our theory.     

许昌市2010年麻疹疫情分析

研究许昌市麻疹流行特征,为消除麻疹提供科学依据.对许昌市2010年麻疹疫情进行描述流行病学分析.结果显示2010年全市共报告麻疹确诊病例158例,报告发病率为3.74/10万;流行毒株为麻疹病毒H1a基因型.3-5月份是发病高峰;0～3岁龄儿童为主,其中小于8月龄病例占报告发病数的32.91％;8- 17月龄病例,68...     

Backward bifurcation of an epidemic model with treatment

An epidemic model with a limited resource for treatment is proposed to understand the effect of the capacity for treatment. It is assumed that treatment rate is proportional to the number of infectives below the capacity and is a constant when the number of infectives is greater than the capacity. It is found that a backward bifurcation occurs if the capacity is small. It is also found that there exist bistable endemic equilibria if the capacity is low.     

Stochastic dynamics in exotic and native blowflies: an analysis combining laboratory experiments and a two-patch metapopulation model

In this study we explored the stochastic population dynamics of three exotic blowfly species, Chrysomya albiceps, Chrysomya megacephala and Chrysomya putoria, and two native species, Cochliomyia macellaria and Lucilia eximia, by combining a density-dependent growth model with a two-patch metapopulation model. Stochastic fecundity, survival and migration were investigated by permitting random variations between predetermined demographic boundary values based on experimental data. Lucilia eximia and Chrysomya albiceps were the species most susceptible to the risk of local extinction. Cochliomyia macellaria, C. megacephala and C. putoria exhibited lower risks of extinction when compared to the other species. The simultaneous analysis of stochastic fecundity and survival revealed an increase in the extinction risk for all species. When stochastic fecundity, survival and migration were simulated together, the coupled populations were synchronized in the five species. These results are discussed, emphasizing biological invasion and interspecific interaction dynamics.     

Subharmonic bifurcation in an S-I-R epidemic model

An S leads to I leads to R epidemic model with annual oscillation in the contact rate is analyzed for the existence of subharmonic solutions of period two years. We prove that a stable period two solution bifurcates from a period one solution as the amplitude of oscillation in the contact rate exceeds a threshold value. This makes rigorous earlier formal arguments of Z. Grossman, I. Gumowski, and K. Dietz [4].     

Analysis of an SEIRS epidemic model with two delays

 A disease transmission model of SEIRS type with exponential demographic structure is formulated. All newborns are assumed susceptible, there is a natural death rate constant, and an excess death rate constant for infective individuals. Latent and immune periods are assumed to be constants, and the force of infection is assumed to be of the standard form, namely proportional to I(t)/N(t) where N(t) is the total (variable) population size and I(t) is the size of the infective population. The model consists of a set of integro-differential equations. Stability of the disease free proportion equilibrium, and existence, uniqueness, and stability of an endemic proportion equilibrium, are investigated. The stability results are stated in terms of a key threshold parameter. More detailed analyses are given for two cases, the SEIS model (with no immune period), and the SIRS model (with no latent period). Several threshold parameters quantify the two ways that the disease can be controlled, by forcing the number or the proportion of infectives to zero. Received 8 May 1995; received in revised form 7 November 1995     

Outbreak analysis of an SIS epidemic model with rewiring

This paper is devoted to the analysis of the early dynamics of an SIS epidemic model defined on networks. The model, introduced by Gross et al. (Phys Rev Lett 96:208701, 2006), is based on the pair-approximation formalism and assumes that, at a given rewiring rate, susceptible nodes replace an infected neighbour by a new susceptible neighbour randomly selected among the pool of susceptible nodes in the population. The analysis uses a triple closure that improves the widely assumed in epidemic models defined on regular and homogeneous networks, and applies it to better understand the early epidemic spread on Poisson, exponential, and scale-free networks. Two extinction scenarios, one dominated by transmission and the other one by rewiring, are characterized by considering the limit system of the model equations close to the beginning of the epidemic. Moreover, an analytical condition for the occurrence of a bistability region is obtained.     

Competition among the pioneers in a seasonal soft-bottom benthic succession: field experiments and analysis of the Gilpin-Ayala competition model

Summary Controlled experiments, designed to assess the effects of pioneers on succession on an intertidal sandflat, provided evidence for interspecific competition between juvenile Hobsonia florida (Polychaeta, Ampharetidae) and oligochaetes. The field data were fitted to both the linear Volterra and non-linear Gilpin-Ayala competition equations. With its greater number of parameters, the Gilpin-Ayala model must provide a better fit to observed population abundances. The Gilpin-Ayala model is flawed as an explanation of the population trajectories of the H. florida and oligochaetes, because its non-linearity parameter affects only intraspecific competion. With either model our field data demonstrate a solution to Hutchinson's paradox. With competition coefficients near unity and similar carrying capacities, the predicted population trajectories are heavily dependent on initial conditions. The predicted times to competitive exclusion are long and can easily exceed the typical period of environmental constancy. Our study offers evidence for Neill's competitive bottleneck: competition acts primarily on the developmental stages of one of a pair of competing species. The permanent meiofauna may act as a competitive bottleneck for the population growth of benthic macrofauna. The mechanism of this competitive interaction probably involves exploitative interspecific competition for benthic diatoms.     

Evolutionary dynamics in an SI epidemic model with phenotype-structured susceptible compartment

When modeling infectious diseases, it is common to assume that infection-derived immunity is either (1) non-existent or (2) perfect and lifelong. However there are many diseases in which infection-derived immunity is known to be present but imperfect. There are various ways in which infection-derived immunity can fail, which can ultimately impact the probability that an individual be reinfected by the same pathogen, as well as the long-run population-level prevalence of the pathogen. Here we discuss seven different models of imperfect infection-derived immunity, including waning, leaky and all-or-nothing immunity. For each model we derive the probability that an infected individual becomes reinfected during their lifetime, given that the system is at endemic equilibrium. This can be thought of as the impact that each of these infection-derived immunity failures have on reinfection. This measure is useful because it provides us with a way to compare different modes of failure of infection-derived immunity.

     

Progression age enhanced backward bifurcation in an epidemic model with super-infection

 We consider a model for a disease with a progressing and a quiescent exposed class and variable susceptibility to super-infection. The model exhibits backward bifurcations under certain conditions, which allow for both stable and unstable endemic states when the basic reproduction number is smaller than one. Received: 11 October 2001 / Revised version: 17 September 2002 / Published online: 17 January 2003 Present address: Department of Biological Statistics and Computational Biology, 434 Warren Hall, Cornell University, Ithaca, NY 14853-7801 This author was visiting Arizona State University when most of the research was done. Research partially supported by NSF grant DMS-0137687. This author's research was partially supported by NSF grant DMS-9706787. Key words or phrases: Backward bifurcation – Multiple endemic equilibria – Alternating stability – Break-point density – Super-infection – Dose-dependent latent period – Progressive and quiescent latent stages – Progression age structure – Threshold type disease activation – Operator semigroups – Hille-Yosida operators – Dynamical systems – Persistence – Global compact attractor