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Computational Epidemiology: Data-Driven Modeling of COVID-19 by Ellen Kuhl 9783030828899

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Description

This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and as a monograph for researchers and scientists. As a textbook, it can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming.

Book Information
ISBN 9783030828899
Author Ellen Kuhl
Format Hardback
Imprint Springer Nature Switzerland AG
Publisher Springer Nature Switzerland AG
Weight(grams) 155g

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