Hughes, James. creator author. aut http://id.loc.gov/vocabulary/relators/aut Houghten, Sheridan. author. aut http://id.loc.gov/vocabulary/relators/aut Dubé, Michael. author. aut http://id.loc.gov/vocabulary/relators/aut Ashlock, Daniel. author. aut http://id.loc.gov/vocabulary/relators/aut Brown, Joseph Alexander. author. aut http://id.loc.gov/vocabulary/relators/aut Ashlock, Wendy. author. aut http://id.loc.gov/vocabulary/relators/aut Stoodley, Matthew. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

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access XI, 97 p. 57 illus., 35 illus. in color. online resource. This book presents algorithms and tools that are designed to model and extract information from personal contact networks that 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. In addition, this book: 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 About the Authors: James Alexander Hughes, Ph.D., is a Professor in the Department of Computer Science at St. Francis Xavier University. Sheridan Houghten, Ph.D., is a Professor in the Department of Computer Science at Brock University. Michael Dubé is a Ph.D. student at the University of Guelph. He earned his Master’s degree from Brock University. Matthew Stoodley, Ph.D., is a Senior Bioinformatics Analyst at the University Health Network in Toronto. Daniel Ashlock, Ph.D., was the Chair of the Department of Mathematics and Statistics at the University of Guelph. Joseph Alexander Brown, Ph.D., is an Assistant Teaching Professor at Thompson Rivers University. Chapter 1 Introduction -- Chapter 2 Evolutionary Computation -- Chapter 3 Graph Compression -- Chapter 4 Network Induction. by James Hughes, Sheridan Houghten, Michael Dubé, Daniel Ashlock, Joseph Alexander Brown, Wendy Ashlock, Matthew Stoodley. Artificial intelligence Machine learning Medical sciences Public health Application software Algorithms Artificial Intelligence Machine Learning Health Sciences Public Health Computer and Information Systems Applications Algorithms Q334-342 TA347.A78 9783031643736 https://doi.org/10.1007/978-3-031-64373-6 https://doi.org/10.1007/978-3-031-64373-6 240925 20251030113103.0 978-3-031-64373-6