Analysis and Simulations of Network-Based Nonlinear Epidemic Models

Madhab Bharman

Analysis and Simulations of Network-Based Nonlinear Epidemic Models - Mathematic, Aug 2024. - 205p; xix:

The study of epidemic dynamics is crucial for understanding and controlling the spread

Finally, our work contributes to the evolving field of epidemic modeling by integrating
graph Laplacian diffusion into the framework.

The study of epidemic dynamics is crucial for understanding and controlling the spread

of infectious diseases. In recent years, there has been a growing interest in employ-
ing graph theory and network science to model the complex interactions among in-
dividuals and understand spatial disease spread in a population. This thesis explores

the application of graph Laplacian diffusion in epidemic modeling of well-established

epidemic models such as Susceptible-Infectious-Removed (SIR), Susceptible-Exposed-
Infectious-Removed (SEIR), Susceptible-Asymptomatic-Infectious-Removed (SAIR),

and more.

Hopf bifurcation; Epidemic; Compartmental Model; Spatial- disease spread; Population mobility; Graph Laplacian; Local Sta- bilith;

517.988 MAD

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