Computational epidemiology : data-driven modeling of COVID-19 / Ellen Kuhl.
Kuhl, Ellen, 1971- author.
2021
RA644.C67 K85 2021
Available Online

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Title Computational epidemiology : data-driven modeling of COVID-19 / Ellen Kuhl.
Author Kuhl, Ellen, 1971- author.
ISBN 9783030828905 (electronic bk.)
3030828905 (electronic bk.)
9783030828899
3030828891
DOI https://doi.org/10.1007/978-3-030-82890-5
Published Cham : Springer, [2021]
Copyright ©2021
Language English
Description 1 online resource
Item Number 10.1007/978-3-030-82890-5 doi
Call Number RA644.C67 K85 2021
Dewey Decimal Classification 614.5/92414
Summary 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 a monograph for researchers and scientists. 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. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 11, 2021).
Available in Other Form Print version: 9783030828899
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table of contents
introduction
infectious diseases
a brief history of infectious diseases
II. mathematical epidemiology
introduction to compartment modeling
compartment modeling of epidemiology
concepts of endemic disease modeling
data-driven modeling in epidemiology.
compartment modeling of COVID19
early outbreak dynamics of COVID-19
asymptomatic transmission of COVID-19
inferring outbreak dynamics of COVID-19
modeling outbreak control
managing infectious diseases
change-point modeling of COVID-19
dynamic compartment modeling of COVID-19
network modeling of epidemiology
network modeling of epidemic processes
network modeling of COVID-19
dynamic network modeling of COVID-19
informing political decision making through modeling
exit strategies from lockdown
vaccination strategies
the second wave
lessons learned.

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