Propagation Dynamics on Complex Networks
Providing an introduction of general epidemic models, Propagation Dynamics on
Complex Networks explores emerging topics of epidemic dynamics on complex
networks, including theories, methods, and real-world applications with elementary and
wide-coverage. This valuable text for researchers and students explores models evolving
over complex networks and presents results concerning dynamics of Network-based models on
a macroscopic scale. The text presents the fundamental knowledge needed to demonstrate how
epidemic dynamical networks can be modeled, analyzed, and controlled along the
state-of-the-art and recent progress in the field and related issues arising from various
epidemic systems.
Preface xi Summary xiii
1 Introduction 1 1.1 Motivation and background 1 1.2 A brief history of mathematical
epidemiology 2 1.3 Organization of the book 5 References 6
2 Various epidemic models on complex networks 10 2.1 Multiple stage models 10 2.2
Staged progression models 13 2.3 Stochastic SIS model 17 2.4 Models with population
mobility 19 2.5 Models in meta-populations 22 2.6 Models with effective contacts 24 2.7
Models with two distinct routes 26 2.8 Models with competing strains 28 2.9 Models with
competing strains and saturated infectivity 31 2.10 Models with birth and death of nodes
and links 33 2.11 Models on weighted networks 34 2.12 Models on directed networks 38 2.13
Models on colored networks 40 2.14 Discrete epidemic models 44 References 47
3 Epidemic threshold analysis 53 3.1 Threshold analysis by the direct method 53 3.2
Epidemic spreading efficiency threshold and epidemic threshold 69 3.3 Epidemic thresholds
and basic reproduction numbers 76 References 98
4 Networked models for SARS and avian influenza 101 4.1 Network models of real diseases
101 4.2 Plausible models for propagation of the SARS virus 102 4.3 Clustering model for
SARS transmission: Application to epidemic control and risk assessment 108 4.4 Small-world
and scale-free models for SARS transmission 114 4.5 Super-spreaders and the rate of
transmission 118 4.6 Scale-free distribution of avian influenza outbreaks 124 4.7
Stratified model of ordinary influenza 130 References 136
5 Infectivity functions 139 5.1 A model with nontrivial infectivity function 140 5.2
Saturated infectivity 143 5.3 Nonlinear infectivity for SIS model on scale-free networks
143 References 148
6 SIS models with an infective medium 150 6.1 SIS model with an infective medium 150
6.2 A modified SIS model with an infective medium 159 6.3 Epidemic models with vectors
between two separated networks 162 6.4 Epidemic transmission on interdependent networks
167 6.4.1 Theoretical modeling 168 6.5 Discussions and remarks 179 References 181
7 Epidemic control and awareness 184 7.1 SIS model with awareness 184 7.2 Discrete-time
SIS model with awareness 192 7.3 Spreading dynamics of a disease-awareness SIS model on
complex networks 198 7.4 Remarks and discussions 201 References 203
8 Adaptive mechanism between dynamics and epidemics 207 8.1 Adaptive mechanism between
dynamical synchronization and epidemic behavior on complex networks 207 8.2 Interplay
between collective behavior and spreading dynamics 216 References 228
9 Epidemic control and immunization 231 9.1 SIS model with immunization 231 9.2 Edge
targeted strategy for controlling epidemic spreading on scale-free networks 235 9.3
Remarks and discussions 237 References 239
10 Global stability analysis 240 10.1 Global stability analysis of the modified model
with an infective medium 240 10.2 Global dynamics of the model with vectors between two
separated networks 241 10.3 Global behavior of disease transmission on interdependent
networks 247 10.4 Global behavior of epidemic transmissions 250 10.5 Global attractivity
of a network-based epidemic SIS model 260 10.6 Global stability of an epidemic model with
birth and death and adaptive weights 264 10.7 Global dynamics of a generalized epidemic
model 268 References 274
11 Information diffusion and pathogen propagation 277 11.1 Information diffusion and
propagation on complex networks 277 11.2 Interplay between information of disease
spreading and epidemic dynamics 281 11.3 Discussions and remarks 284 References 286
Appendix A Proofs of theorems 289 A.1 Transition from discrete-time linear system to
continuous-time linear system 289 A.2 Proof of Lemma 6.1 291 A.3 Proof of Theorem 10.4 291
A.4 Proof of Theorem 10.3 292 A.5 Proof of Theorem 10.42 296
Appendix B Further proofs of results 302 B.1 Eigenvalues of the matrix p F in (6.27)
302 B.2 The matrix in (6.32) 304 B.3 Proof of (7.6) in Chapter 7 305 B.4 The positiveness
of ': proof of ' > 0 in Section 9.1.2 306 B.5 The relation between and in Section 9.1.3
308 Index 311
328 pages, Hardcover