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Computational Epidemiology - From Disease Transmission Modeling to Vaccination Decision Making (Hardcover, 1st ed. 2020)
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Computational Epidemiology - From Disease Transmission Modeling to Vaccination Decision Making (Hardcover, 1st ed. 2020)
Series: Health Information Science
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This book provides a comprehensive introduction to computational
epidemiology, highlighting its major methodological paradigms
throughout the development of the field while emphasizing the needs
for a new paradigm shift in order to most effectively address the
increasingly complex real-world challenges in disease control and
prevention. Specifically, the book presents the basic concepts,
related computational models, and tools that are useful for
characterizing disease transmission dynamics with respect to a
heterogeneous host population. In addition, it shows how to develop
and apply computational methods to tackle the challenges involved
in population-level intervention, such as prioritized vaccine
allocation. A unique feature of this book is that its examination
on the issues of vaccination decision-making is not confined only
to the question of how to develop strategic policies on prioritized
interventions, as it further approaches the issues from the
perspective of individuals, offering a well integrated cost-benefit
and social-influence account for voluntary vaccination decisions.
One of the most important contributions of this book lies in it
offers a blueprint on a novel methodological paradigm in
epidemiology, namely, systems epidemiology, with detailed systems
modeling principles, as well as practical steps and real-world
examples, which can readily be applied in addressing future systems
epidemiological challenges. The book is intended to serve as a
reference book for researchers and practitioners in the fields of
computer science and epidemiology. Together with the provided
references on the key concepts, methods, and examples being
introduced, the book can also readily be adopted as an introductory
text for undergraduate and graduate courses in computational
epidemiology as well as systems epidemiology, and as training
materials for practitioners and field workers.
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