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Search Results: 1 - 10 of 145801 matches for " Leah B. Shaw "
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Effects of community structure on epidemic spread in an adaptive network
Ilker Tunc,Leah B. Shaw
Physics , 2012,
Abstract: When an epidemic spreads in a population, individuals may adaptively change the structure of their social contact network to reduce risk of infection. Here we study the spread of an epidemic on an adaptive network with community structure. We model the effect of two communities with different average degrees. The disease model is susceptible-infected-susceptible (SIS), and adaptation is rewiring of links between susceptibles and infectives. The bifurcation structure is obtained, and a mean field model is developed that accurately predicts the steady state behavior of the system. We show that an epidemic can alter the community structure.
Asymmetry in the presence of migration stabilizes multistrain disease outbreaks
Simone Bianco,Leah B. Shaw
Quantitative Biology , 2009,
Abstract: We study the effect of migration between coupled populations, or patches, on the stability properties of multistrain disease dynamics. The epidemic model used in this work displays a Hopf bifurcation to oscillations in a single well mixed population. It is shown numerically that migration between two non-identical patches stabilizes the endemic steady state, delaying the onset of large amplitude outbreaks and reducing the total number of infections. This result is motivated by analyzing generic Hopf bifurcations with different frequencies and with diffusive coupling between them. Stabilization of the steady state is again seen, indicating that our observation in the full multistrain model is based on qualitative characteristics of the dynamics rather than on details of the disease model.
Noise induced dynamics in adaptive networks with applications to epidemiology
Leah B. Shaw,Ira B. Schwartz
Physics , 2008,
Abstract: Recent work in modeling the coupling between disease dynamics and dynamic social network geometry has led to the examination of how human interactions force a rewiring of connections in a population. Rewiring of the network may be considered an adaptive response to social forces due to disease spread, which in turn feeds back to the disease dynamics. Such epidemic models, called adaptive networks, have led to new dynamical instabilities along with the creation of multiple attracting states. The co-existence of several attractors is sensitive to internal and external fluctuations, and leads to enhanced stochastic oscillatory outbreaks and disease extinction. The aim of this paper is to explore the bifurcations of adaptive network models in the presence of fluctuations and to review some of the new fluctuation phenomena induced in adaptive networks.
Isochronal synchronization of delay-coupled systems
Ira B. Schwartz,Leah B. Shaw
Physics , 2006, DOI: 10.1103/PhysRevE.75.046207
Abstract: We consider small network models for mutually delay-coupled systems which typically do not exhibit stable isochronally synchronized solutions. We show that for certain coupling architectures which involve delayed self feedback to the nodes, the oscillators become isochronally synchronized. Applications are shown for both incoherent pump coupled lasers and spatio-temporal coupled fiber ring lasers.
Fluctuating epidemics on adaptive networks
Leah B. Shaw,Ira B. Schwartz
Quantitative Biology , 2008, DOI: 10.1103/PhysRevE.77.066101
Abstract: A model for epidemics on an adaptive network is considered. Nodes follow an SIRS (susceptible-infective-recovered-susceptible) pattern. Connections are rewired to break links from non-infected nodes to infected nodes and are reformed to connect to other non-infected nodes, as the nodes that are not infected try to avoid the infection. Monte Carlo simulation and numerical solution of a mean field model are employed. The introduction of rewiring affects both the network structure and the epidemic dynamics. Degree distributions are altered, and the average distance from a node to the nearest infective increases. The rewiring leads to regions of bistability where either an endemic or a disease-free steady state can exist. Fluctuations around the endemic state and the lifetime of the endemic state are considered. The fluctuations are found to exhibit power law behavior.
Enhanced vaccine control of epidemics in adaptive networks
Leah B. Shaw,Ira B. Schwartz
Quantitative Biology , 2009, DOI: 10.1103/PhysRevE.81.046120
Abstract: We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to an interaction between the adaptive network rewiring and the vaccine application. Disease extinction rates using vaccination are computed, and orders of magnitude less vaccine application is needed to drive the disease to extinction in an adaptive network than in a static one.
Asymptotically inspired moment-closure approximation for adaptive networks
Maxim S. Shkarayev,Leah B. Shaw
Quantitative Biology , 2013, DOI: 10.1103/PhysRevE.88.052804
Abstract: Adaptive social networks, in which nodes and network structure co-evolve, are often described using a mean-field system of equations for the density of node and link types. These equations constitute an open system due to dependence on higher order topological structures. We propose a new approach to moment closure based on the analytical description of the system in an asymptotic regime. We apply the proposed approach to two examples of adaptive networks: recruitment to a cause model and adaptive epidemic model. We show a good agreement between the improved mean-field prediction and simulations of the full network system.
Zero Lag Synchronization of Mutually Coupled Lasers in the Presence of Delays
Alexandra S. Landsman,Leah B. Shaw,Ira B. Schwartz
Physics , 2007,
Abstract: We consider a line of three mutually coupled lasers with time delays and study chaotic synchronization of the outer lasers. Two different systems are presented: optoelectronically coupled semiconductor lasers and optically coupled fiber lasers. While the dynamics of the two systems are very different, robust synchronization of end lasers is obtained in both cases over a range of parameters. Here, we present analysis and numerical simulation to explain some of the observed synchronization phenomena. First, we introduce the system of three coupled semiconductor lasers and discuss the onset of oscillations that occurs via a bifurcation as the coupling strength increases. Next, we analyze the synchronization of the end lasers by examining the dynamics transverse to synchronized state. We prove that chaotic synchronization of the outer semiconductor lasers will occur for sufficiently long delays, and we make a comparison to generalized synchronization in driven dissipative systems. It is shown that the stability of synchronous state (as indicated by negative Lyupunov exponents transverse to the synchronization manifold) depends on the internal dissipation of the outer lasers. We next present numerical simulations for three coupled fiber lasers, highlighting some of the differences between the semiconductor and fiber laser systems. Due to the large number of coupled modes in fiber lasers, this is a good system for investigating spatio-temporal chaos. Stochastic noise is included in the fiber laser model, and synchrony of the outer lasers is observed even at very small coupling strengths.
Local Inhomogeneity in Asymmetric Simple Exclusion Processes with Extended Objects
Leah B. Shaw,Anatoly B. Kolomeisky,Kelvin H. Lee
Physics , 2003, DOI: 10.1088/0305-4470/37/6/010
Abstract: Totally asymmetric simple exclusion processes (TASEP) with particles which occupy more than one lattice site and with a local inhomogeneity far away from the boundaries are investigated. These non-equilibrium processes are relevant for the understanding of many biological and chemical phenomena. The steady-state phase diagrams, currents, and bulk densities are calculated using a simple approximate theory and extensive Monte Carlo computer simulations. It is found that the phase diagram for TASEP with a local inhomogeneity is qualitatively similar to homogeneous models, although the phase boundaries are significantly shifted. The complex dynamics is discussed in terms of domain-wall theory for driven lattice systems.
Using dimension reduction to improve outbreak predictability of multistrain diseases
Leah B. Shaw,Lora Billings,Ira B. Schwartz
Physics , 2006,
Abstract: Multistrain diseases have multiple distinct coexisting serotypes (strains). For some diseases, such as dengue fever, the serotypes interact by antibody-dependent enhancement (ADE), in which infection with a single serotype is asymptomatic, but contact with a second serotype leads to higher viral load and greater infectivity. We present and analyze a dynamic compartmental model for multiple serotypes exhibiting ADE. Using center manifold techniques, we show how the dynamics rapidly collapses to a lower dimensional system. Using the constructed reduced model, we can explain previously observed synchrony between certain classes of primary and secondary infectives (Schwartz et al., Phys. Rev. E 72: 066201, 2005). Additionally, we show numerically that the center manifold equations apply even to noisy systems. Both deterministic and stochastic versions of the model enable prediction of asymptomatic individuals that are difficult to track during an epidemic. We also show how this technique may be applicable to other multistrain disease models, such as those with cross-immunity.
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