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050  4 RA652.2.M3.F8 2014eb 
082 0  614.4015118 
100 1  Fu, Xinchu 
245 10 Propagation Dynamics on Complex Networks :|bModels, 
       Methods and Stability Analysis 
250    1st ed 
264  1 New York :|bJohn Wiley & Sons, Incorporated,|c2014 
264  4 |c©2013 
300    1 online resource (330 pages) 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
505 0  Cover -- Title Page -- Copyright -- Contents -- Preface --
       Summary -- Chapter 1 Introduction -- 1.1 Motivation and 
       background -- 1.2 A brief history of mathematical 
       epidemiology -- 1.2.1 Compartmental modeling -- 1.2.2 
       Epidemic modeling on complex networks -- 1.3 Organization 
       of the book -- References -- Chapter 2 Various epidemic 
       models on complex networks -- 2.1 Multiple stage models --
       2.1.1 Multiple susceptible individuals -- 2.1.2 Multiple 
       infected individuals -- 2.1.3 Multiple-staged infected 
       individuals -- 2.2 Staged progression models -- 2.2.1 
       Simple-staged progression model -- 2.2.2 Staged 
       progression model on homogenous networks -- 2.2.3 Staged 
       progression model on heterogenous networks -- 2.2.4 Staged
       progression model with birth and death -- 2.2.5 Staged 
       progression model with birth and death on homogenous 
       networks -- 2.2.6 Staged progression model with birth and 
       death on heterogenous networks -- 2.3 Stochastic SIS model
       -- 2.3.1 A general concept: Epidemic spreading efficiency 
       -- 2.4 Models with population mobility -- 2.4.1 Epidemic 
       spreading without mobility of individuals -- 2.4.2 
       Spreading of epidemic diseases among different cities -- 
       2.4.3 Epidemic spreading within and between cities -- 2.5 
       Models in meta-populations -- 2.5.1 Model formulation -- 
       2.6 Models with effective contacts -- 2.6.1 Epidemics with
       effectively uniform contact -- 2.6.2 Epidemics with 
       effective contact in homogenous and heterogenous networks 
       -- 2.7 Models with two distinct routes -- 2.8 Models with 
       competing strains -- 2.8.1 SIS model with competing 
       strains -- 2.8.2 Remarks and discussions -- 2.9 Models 
       with competing strains and saturated infectivity -- 2.9.1 
       SIS model with mutation mechanism -- 2.9.2 SIS model with 
       super-infection mechanism -- 2.10 Models with birth and 
       death of nodes and links -- 2.11 Models on weighted 
       networks 
505 8  2.11.1 Model with birth and death and adaptive weights -- 
       2.12 Models on directed networks -- 2.13 Models on colored
       networks -- 2.13.1 SIS epidemic models on colored networks
       -- 2.13.2 Microscopic Markov-chain analysis -- 2.14 
       Discrete epidemic models -- 2.14.1 Discrete SIS model with
       nonlinear contagion scheme -- 2.14.2 Discrete-time 
       epidemic model in heterogenous networks -- 2.14.3 A 
       generalized model -- References -- Chapter 3 Epidemic 
       threshold analysis -- 3.1 Threshold analysis by the direct
       method -- 3.1.1 The epidemic rate is B/ni inside the same 
       cities -- 3.1.2 Epidemics on homogenous networks -- 3.1.3 
       Epidemics on heterogenous networks -- 3.2 Epidemic 
       spreading efficiency threshold and epidemic threshold -- 
       3.2.1 The case of 1 ≠ 2 -- 3.2.2 The case of 1 = 2 -- 
       3.2.3 Epidemic threshold in finite populations -- 3.2.4 
       Epidemic threshold in infinite populations -- 3.3 Epidemic
       thresholds and basic reproduction numbers -- 3.3.1 
       Threshold from a self-consistency equation -- 3.3.2 
       Threshold unobtainable from a self-consistency equation --
       3.3.3 Threshold analysis for SIS model with mutation -- 
       3.3.4 Threshold analysis for SIS model with super-
       infection -- 3.3.5 Epidemic thresholds for models on 
       directed networks -- 3.3.6 Epidemic thresholds on 
       technological and social networks -- 3.3.7 Epidemic 
       thresholds on directed networks with immunization -- 3.3.8
       Comparisons of epidemic thresholds for directed networks 
       with immunization -- 3.3.9 Thresholds for colored network 
       models -- 3.3.10 Thresholds for discrete epidemic models -
       - 3.3.11 Basic reproduction number and existence of a 
       positive equilibrium -- References -- Chapter 4 Networked 
       models for SARS and avian influenza -- 4.1 Network models 
       of real diseases -- 4.2 Plausible models for propagation 
       of the SARS virus 
505 8  4.3 Clustering model for SARS transmission: Application to
       epidemic control and risk assessment -- 4.4 Small-world 
       and scale-free models for SARS transmission -- 4.5 Super-
       spreaders and the rate of transmission -- 4.6 Scale-free 
       distribution of avian influenza outbreaks -- 4.7 
       Stratified model of ordinary influenza -- References -- 
       Chapter 5 Infectivity functions -- 5.1 A model with 
       nontrivial infectivity function -- 5.1.1 Epidemic 
       threshold for SIS model with piecewise-linear infectivity 
       -- 5.1.2 Piecewise smooth and nonlinear infectivity -- 5.2
       Saturated infectivity -- 5.3 Nonlinear infectivity for SIS
       model on scale-free networks -- 5.3.1 The epidemic 
       threshold for SIS model on scale-free networks with 
       nonlinear infectivity -- 5.3.2 Discussions and remarks -- 
       References -- Chapter 6 SIS models with an infective 
       medium -- 6.1 SIS model with an infective medium -- 6.1.1 
       Homogenous complex networks -- 6.1.2 Scale-free networks: 
       The Barabási-Albert model -- 6.1.3 Uniform immunization 
       strategy -- 6.1.4 Optimized immunization strategies -- 6.2
       A modified SIS model with an infective medium -- 6.2.1 The
       modified model -- 6.2.2 Epidemic threshold for the 
       modified model with an infective medium -- 6.3 Epidemic 
       models with vectors between two separated networks -- 
       6.3.1 Model formulation -- 6.3.2 Basic reproduction number
       -- 6.3.3 Sensitivity analysis -- 6.4 Epidemic transmission
       on interdependent networks -- 6.4.1 Theoretical modeling -
       - 6.4.2 Mathematical analysis of epidemic dynamics -- 
       6.4.3 Numerical analysis: Effect of model parameters on 
       the basic reproduction number -- 6.4.4 Numerical analysis:
       Effect of model parameters on infected node densities -- 
       6.5 Discussions and remarks -- References -- Chapter 7 
       Epidemic control and awareness -- 7.1 SIS model with 
       awareness -- 7.1.1 Background -- 7.1.2 The model -- 7.1.3 
       Epidemic threshold 
505 8  7.1.4 Conclusions and discussions -- 7.2 Discrete-time SIS
       model with awareness -- 7.2.1 SIS model with awareness 
       interactions -- 7.2.2 Theoretical analysis: Basic 
       reproduction number -- 7.2.3 Remarks and discussions -- 
       7.3 Spreading dynamics of a disease-awareness SIS model on
       complex networks -- 7.3.1 Model formulation -- 7.3.2 
       Derivation of limiting systems -- 7.3.3 Basic reproduction
       number and local stability -- 7.4 Remarks and discussions 
       -- References -- Chapter 8 Adaptive mechanism between 
       dynamics and epidemics -- 8.1 Adaptive mechanism between 
       dynamical synchronization and epidemic behavior on complex
       networks -- 8.1.1 Models of complex dynamical network and 
       epidemic network -- 8.1.2 Models of epidemic 
       synchronization and its analysis -- 8.1.3 Local stability 
       of epidemic synchronization -- 8.1.4 Global stability of 
       epidemic synchronization -- 8.2 Interplay between 
       collective behavior and spreading dynamics -- 8.2.1 A 
       general bidirectional model -- 8.2.2 Global 
       synchronization and spreading dynamics -- 8.2.3 Stability 
       of global synchronization and spreading dynamics -- 8.2.4 
       Phase synchronization and spreading dynamics -- 8.2.5 
       Control of spreading networks -- 8.2.6 Discussions and 
       remarks -- References -- Chapter 9 Epidemic control and 
       immunization -- 9.1 SIS model with immunization -- 9.1.1 
       Proportional immunization -- 9.1.2 Targeted immunization -
       - 9.1.3 Acquaintance immunization -- 9.1.4 Active 
       immunization -- 9.2 Edge targeted strategy for controlling
       epidemic spreading on scale-free networks -- 9.3 Remarks 
       and discussions -- References -- Chapter 10 Global 
       stability analysis -- 10.1 Global stability analysis of 
       the modified model with an infective medium -- 10.2 Global
       dynamics of the model with vectors between two separated 
       networks -- 10.2.1 Global stability of the disease-free 
       equilibrium and existence of the endemic equilibrium 
505 8  10.2.2 Uniqueness and global attractivity of the endemic 
       equilibrium -- 10.3 Global behavior of disease 
       transmission on interdependent networks -- 10.3.1 
       Existence and global stability of the endemic equilibrium 
       for a disease-awareness SIS model -- 10.4 Global behavior 
       of epidemic transmissions -- 10.4.1 Stability of the model
       equilibria -- 10.4.2 Stability analysis for discrete 
       epidemic models -- 10.4.3 Global stability of the disease-
       free equilibrium -- 10.4.4 Global attractiveness of 
       epidemic disease -- 10.5 Global attractivity of a network-
       based epidemic SIS model -- 10.5.1 Positiveness, 
       boundedness and equilibria -- 10.5.2 Global attractivity 
       of the model -- 10.5.3 Remarks and discussions -- 10.6 
       Global stability of an epidemic model with birth and death
       and adaptive weights -- 10.6.1 Global dynamics of the 
       model -- 10.6.2 Discussions and remarks -- 10.7 Global 
       dynamics of a generalized epidemic model -- 10.7.1 Model 
       formulation -- 10.7.2 Global dynamics of the model -- 
       10.7.3 Discussions and remarks -- References -- Chapter 11
       Information diffusion and pathogen propagation -- 11.1 
       Information diffusion and propagation on complex networks 
       -- 11.1.1 Information diffusion on complex networks -- 
       11.1.2 Some essential differences between information 
       propagation and epidemic spreading -- 11.2 Interplay 
       between information of disease spreading and epidemic 
       dynamics -- 11.2.1 Preliminaries -- 11.2.2 Theoretical 
       analysis of the model -- 11.3 Discussions and remarks -- 
       References -- Appendix A Proofs of theorems -- A.1 
       Transition from discrete-time linear system to continuous-
       time linear system -- A.2 Proof of Lemma 6.1 -- A.3 Proof 
       of Theorem 10.4 -- A.4 Proof of Theorem 10.3 -- A.5 Proof 
       of Theorem 10.42 -- Appendix B Further proofs of results -
       - B.1 Eigenvalues of the matrix F in (6.27) -- B.2 The 
       matrix T in (6.32) -- B.3 Proof of (7.6) in Chapter 7 
505 8  B.4 The positiveness of ð': proof of ð' > 0 in Sec 9.1.2 
520    Explores the emerging subject of epidemic dynamics on 
       complex networks, including theories, methods, and real-
       world applications Throughout history epidemic diseases 
       have presented a serious threat to human life, and in 
       recent years the spread of infectious diseases such as 
       dengue, malaria, HIV, and SARS has captured global 
       attention; and in the modern technological age, the 
       proliferation of virus attacks on the Internet highlights 
       the emergent need for knowledge about modeling, analysis, 
       and control in epidemic dynamics on complex networks.  For
       advancement of techniques, it has become clear that more 
       fundamental knowledge will be needed in mathematical and 
       numerical context about how epidemic dynamical networks 
       can be modelled, analyzed, and controlled. This book 
       explores recent progress in these topics and looks at 
       issues relating to various epidemic systems. Propagation 
       Dynamics on Complex Networks covers most key topics in the
       field, and will provide a valuable resource for graduate 
       students and researchers interested in network science and
       dynamical systems, and related interdisciplinary fields. 
       Key Features: Includes a brief history of mathematical 
       epidemiology and epidemic modeling on complex networks. 
       Explores how information, opinion, and rumor spread via 
       the Internet and social networks. Presents plausible 
       models for propagation of SARS and avian influenza 
       outbreaks, providing a reality check for otherwise 
       abstract mathematical modeling. Considers various 
       infectivity functions, including constant, piecewise-
       linear, saturated, and nonlinear cases. Examines 
       information transmission on complex networks, and 
       investigates the difference between information and 
       epidemic spreading 
588    Description based on publisher supplied metadata and other
       sources 
590    Electronic reproduction. Ann Arbor, Michigan : ProQuest 
       Ebook Central, 2020. Available via World Wide Web. Access 
       may be limited to ProQuest Ebook Central affiliated 
       libraries 
650  0 Epidemiology -- Mathematical models.;Epidemiology -- 
       Methodology.;Biomathematics 
655  4 Electronic books 
700 1  Small, Michael 
700 1  Chen, Guanrong 
776 08 |iPrint version:|aFu, Xinchu|tPropagation Dynamics on 
       Complex Networks : Models, Methods and Stability Analysis
       |dNew York : John Wiley & Sons, Incorporated,c2014
       |z9781118534502 
856 40 |uhttps://ebookcentral.proquest.com/lib/sinciatw/
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