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Computational Epidemiology : Data-Driven Modeling of COVID-19 /

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....

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Bibliographic Details
Main Author: Kuhl, Ellen (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Subjects:
Biomedical engineering.
Bioinformatics.
Epidemiology.
Mathematical models.
Biomedical Engineering and Bioengineering.
Mathematical Modeling and Industrial Mathematics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 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.