AI Versus Epidemics

This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.

• Demonstrates applied techniques for researchers and professionals working on solving problems related to epidemics
• Explains why personal contact networks are the key to understanding the dynamics of an epidemic managing related issues
• Provides solutions to problems that occur when creating and utilizing models of large populations